--- _id: '9192' abstract: - lang: eng text: Here are the research data underlying the publication " Effects of fine-scale population structure on inbreeding in a long-term study of snapdragons (Antirrhinum majus)." Further information are summed up in the README document. article_processing_charge: No author: - first_name: Parvathy full_name: Surendranadh, Parvathy id: 455235B8-F248-11E8-B48F-1D18A9856A87 last_name: Surendranadh orcid: 0000-0001-6395-386X - first_name: Louise S full_name: Arathoon, Louise S id: 2CFCFF98-F248-11E8-B48F-1D18A9856A87 last_name: Arathoon orcid: 0000-0003-1771-714X - first_name: Carina full_name: Baskett, Carina id: 3B4A7CE2-F248-11E8-B48F-1D18A9856A87 last_name: Baskett orcid: 0000-0002-7354-8574 - first_name: David full_name: Field, David id: 419049E2-F248-11E8-B48F-1D18A9856A87 last_name: Field orcid: 0000-0002-4014-8478 - first_name: Melinda full_name: Pickup, Melinda id: 2C78037E-F248-11E8-B48F-1D18A9856A87 last_name: Pickup orcid: 0000-0001-6118-0541 - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 citation: ama: Surendranadh P, Arathoon LS, Baskett C, Field D, Pickup M, Barton NH. Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus. 2021. doi:10.15479/AT:ISTA:9192 apa: Surendranadh, P., Arathoon, L. S., Baskett, C., Field, D., Pickup, M., & Barton, N. H. (2021). Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:9192 chicago: Surendranadh, Parvathy, Louise S Arathoon, Carina Baskett, David Field, Melinda Pickup, and Nicholas H Barton. “Effects of Fine-Scale Population Structure on the Distribution of Heterozygosity in a Long-Term Study of Antirrhinum Majus.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/AT:ISTA:9192. ieee: P. Surendranadh, L. S. Arathoon, C. Baskett, D. Field, M. Pickup, and N. H. Barton, “Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus.” Institute of Science and Technology Austria, 2021. ista: Surendranadh P, Arathoon LS, Baskett C, Field D, Pickup M, Barton NH. 2021. Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus, Institute of Science and Technology Austria, 10.15479/AT:ISTA:9192. mla: Surendranadh, Parvathy, et al. Effects of Fine-Scale Population Structure on the Distribution of Heterozygosity in a Long-Term Study of Antirrhinum Majus. Institute of Science and Technology Austria, 2021, doi:10.15479/AT:ISTA:9192. short: P. Surendranadh, L.S. Arathoon, C. Baskett, D. Field, M. Pickup, N.H. Barton, (2021). contributor: - contributor_type: project_member first_name: Parvathy id: 455235B8-F248-11E8-B48F-1D18A9856A87 last_name: Surendranadh - contributor_type: project_member first_name: Louise S id: 2CFCFF98-F248-11E8-B48F-1D18A9856A87 last_name: Arathoon - contributor_type: project_member first_name: Carina id: 3B4A7CE2-F248-11E8-B48F-1D18A9856A87 last_name: Baskett - contributor_type: project_member first_name: David id: 419049E2-F248-11E8-B48F-1D18A9856A87 last_name: Field orcid: 0000-0002-4014-8478 - contributor_type: project_member first_name: Melinda id: 2C78037E-F248-11E8-B48F-1D18A9856A87 last_name: Pickup orcid: 0000-0001-6118-0541 - contributor_type: project_leader first_name: Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 date_created: 2021-02-24T17:49:21Z date_published: 2021-02-26T00:00:00Z date_updated: 2025-04-15T08:20:40Z day: '26' ddc: - '576' department: - _id: GradSch - _id: NiBa doi: 10.15479/AT:ISTA:9192 file: - access_level: open_access checksum: f85537815809a8a4b7da9d01163f88c0 content_type: application/x-zip-compressed creator: larathoo date_created: 2021-02-24T17:45:13Z date_updated: 2021-02-24T17:45:13Z file_id: '9193' file_name: Data_Code.zip file_size: 5934452 relation: main_file success: 1 file_date_updated: 2021-02-24T17:45:13Z fulldoi: https://doi.org/10.15479/AT:ISTA:9192 has_accepted_license: '1' license: https://creativecommons.org/licenses/by/4.0/ month: '02' oa: 1 oa_version: Published Version publisher: Institute of Science and Technology Austria related_material: record: - id: '8254' relation: earlier_version status: public - id: '11321' relation: later_version status: public - id: '11411' relation: used_in_publication status: public status: public title: Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '9323' abstract: - lang: eng text: This .zip File contains the data for figures presented in the main text and supplementary material of "A singlet triplet hole spin qubit in planar Ge" by D. Jirovec, et. al. The measurements were done using Labber Software and the data is stored in the hdf5 file format. The files can be opened using either the Labber Log Browser (https://labber.org/overview/) or Labber Python API (http://labber.org/online-doc/api/LogFile.html). A single file is acquired with QCodes and features the corresponding data type. XRD data are in .dat format and a code to open the data is provided. The code for simulations is as well provided in Python. article_processing_charge: No author: - first_name: Daniel full_name: Jirovec, Daniel id: 4C473F58-F248-11E8-B48F-1D18A9856A87 last_name: Jirovec orcid: 0000-0002-7197-4801 citation: ama: Jirovec D. Research data for “A singlet-triplet hole spin qubit planar Ge.” 2021. doi:10.15479/AT:ISTA:9323 apa: Jirovec, D. (2021). Research data for “A singlet-triplet hole spin qubit planar Ge.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:9323 chicago: Jirovec, Daniel. “Research Data for ‘A Singlet-Triplet Hole Spin Qubit Planar Ge.’” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/AT:ISTA:9323. ieee: D. Jirovec, “Research data for ‘A singlet-triplet hole spin qubit planar Ge.’” Institute of Science and Technology Austria, 2021. ista: Jirovec D. 2021. Research data for ‘A singlet-triplet hole spin qubit planar Ge’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:9323. mla: Jirovec, Daniel. Research Data for “A Singlet-Triplet Hole Spin Qubit Planar Ge.” Institute of Science and Technology Austria, 2021, doi:10.15479/AT:ISTA:9323. short: D. Jirovec, (2021). contributor: - contributor_type: project_member first_name: Daniel id: 4C473F58-F248-11E8-B48F-1D18A9856A87 last_name: Jirovec date_created: 2021-04-14T09:50:22Z date_published: 2021-04-14T00:00:00Z date_updated: 2025-06-12T06:57:18Z day: '14' ddc: - '530' department: - _id: GradSch - _id: GeKa doi: 10.15479/AT:ISTA:9323 file: - access_level: open_access checksum: c569d2a2ce1694445cdbca19cf8ae023 content_type: application/x-zip-compressed creator: djirovec date_created: 2021-04-14T09:48:47Z date_updated: 2021-04-14T09:48:47Z file_id: '9324' file_name: DataRepositorySTqubit.zip file_size: 221832287 relation: main_file success: 1 - access_level: open_access checksum: 845bdf87430718ad6aff47eda7b5fc92 content_type: application/octet-stream creator: djirovec date_created: 2021-04-14T09:49:30Z date_updated: 2021-04-14T09:49:30Z file_id: '9325' file_name: ReadMe file_size: 4323 relation: main_file success: 1 file_date_updated: 2021-04-14T09:49:30Z fulldoi: https://doi.org/10.15479/AT:ISTA:9323 has_accepted_license: '1' license: https://creativecommons.org/publicdomain/zero/1.0/ month: '04' oa: 1 oa_version: Published Version publisher: Institute of Science and Technology Austria related_material: record: - id: '8909' relation: used_in_publication status: public status: public title: Research data for "A singlet-triplet hole spin qubit planar Ge" tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '9327' abstract: - lang: eng text: "This archive contains the missing sweater mesh animations and displacement models for the code of \"Mechanics-Aware Deformation of Yarn Pattern Geometry\"\r\n\r\nCode Repository: https://git.ist.ac.at/gsperl/MADYPG" author: - first_name: Georg full_name: Sperl, Georg id: 4DD40360-F248-11E8-B48F-1D18A9856A87 last_name: Sperl - first_name: Rahul full_name: Narain, Rahul last_name: Narain - first_name: Christopher J full_name: Wojtan, Christopher J id: 3C61F1D2-F248-11E8-B48F-1D18A9856A87 last_name: Wojtan orcid: 0000-0001-6646-5546 citation: ama: Sperl G, Narain R, Wojtan C. Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data). 2021. doi:10.15479/AT:ISTA:9327 apa: Sperl, G., Narain, R., & Wojtan, C. (2021). Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data). IST Austria. https://doi.org/10.15479/AT:ISTA:9327 chicago: Sperl, Georg, Rahul Narain, and Chris Wojtan. “Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data).” IST Austria, 2021. https://doi.org/10.15479/AT:ISTA:9327. ieee: G. Sperl, R. Narain, and C. Wojtan, “Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data).” IST Austria, 2021. ista: Sperl G, Narain R, Wojtan C. 2021. Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data), IST Austria, 10.15479/AT:ISTA:9327. mla: Sperl, Georg, et al. Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data). IST Austria, 2021, doi:10.15479/AT:ISTA:9327. short: G. Sperl, R. Narain, C. Wojtan, (2021). date_created: 2021-04-16T14:26:19Z date_published: 2021-05-01T00:00:00Z date_updated: 2026-06-18T19:57:47Z ddc: - '005' department: - _id: GradSch - _id: ChWo doi: 10.15479/AT:ISTA:9327 file: - access_level: open_access checksum: 0324cb519273371708743f3282e7c081 content_type: application/zip creator: gsperl date_created: 2021-04-16T14:15:12Z date_updated: 2021-04-16T14:15:12Z file_id: '9328' file_name: MADYPG_extra_data.zip file_size: 802586232 relation: main_file success: 1 - access_level: open_access checksum: 4c224551adf852b136ec21a4e13f0c1b content_type: application/gzip creator: pub-gitlab-bot date_created: 2021-04-26T09:33:44Z date_updated: 2021-04-26T09:33:44Z file_id: '9353' file_name: MADYPG.zip file_size: 64962865 relation: main_file file_date_updated: 2021-04-26T09:33:44Z fulldoi: https://doi.org/10.15479/AT:ISTA:9327 gitlab_commit_id: 6a77e7e22769230ae5f5edaa090fb4b828e57573 gitlab_url: https://git.ist.ac.at/gsperl/MADYPG has_accepted_license: '1' license: https://opensource.org/licenses/MIT month: '05' oa: 1 publisher: IST Austria related_material: record: - id: '9818' relation: used_for_analysis_in status: public status: public title: Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data) tmp: legal_code_url: https://opensource.org/licenses/MIT name: The MIT License short: MIT type: software user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2021' ... --- _id: '9389' abstract: - lang: eng text: "This .zip File contains the transport data for \"Non-topological zero bias peaks in full-shell nanowires induced by flux tunable Andreev states\" by M. Valentini, et. al. \r\nThe measurements were done using Labber Software and the data is stored in the hdf5 file format.\r\nInstructions of how to read the data are in \"Notebook_Valentini.pdf\"." acknowledged_ssus: - _id: NanoFab article_processing_charge: No author: - first_name: Marco full_name: Valentini, Marco id: C0BB2FAC-D767-11E9-B658-BC13E6697425 last_name: Valentini citation: ama: Valentini M. Research data for “Non-topological zero bias peaks in full-shell nanowires induced by flux tunable Andreev states.” 2021. doi:10.15479/AT:ISTA:9389 apa: Valentini, M. (2021). Research data for “Non-topological zero bias peaks in full-shell nanowires induced by flux tunable Andreev states.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:9389 chicago: Valentini, Marco. “Research Data for ‘Non-Topological Zero Bias Peaks in Full-Shell Nanowires Induced by Flux Tunable Andreev States.’” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/AT:ISTA:9389. ieee: M. Valentini, “Research data for ‘Non-topological zero bias peaks in full-shell nanowires induced by flux tunable Andreev states.’” Institute of Science and Technology Austria, 2021. ista: Valentini M. 2021. Research data for ‘Non-topological zero bias peaks in full-shell nanowires induced by flux tunable Andreev states’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:9389. mla: Valentini, Marco. Research Data for “Non-Topological Zero Bias Peaks in Full-Shell Nanowires Induced by Flux Tunable Andreev States.” Institute of Science and Technology Austria, 2021, doi:10.15479/AT:ISTA:9389. short: M. Valentini, (2021). contributor: - contributor_type: contact_person first_name: Marco id: C0BB2FAC-D767-11E9-B658-BC13E6697425 last_name: Valentini date_created: 2021-05-14T12:07:53Z date_published: 2021-01-01T00:00:00Z date_updated: 2025-06-12T06:32:43Z ddc: - '530' department: - _id: GradSch - _id: GeKa doi: 10.15479/AT:ISTA:9389 file: - access_level: open_access checksum: 80a905c4eef24dab6fb247e81a3d67f5 content_type: application/pdf creator: mvalenti date_created: 2021-05-14T11:42:23Z date_updated: 2021-05-14T11:42:23Z file_id: '9390' file_name: Notebook_Valentini.pdf file_size: 10572981 relation: main_file - access_level: open_access checksum: 1e61a7e63949448a8db0091cdac23570 content_type: application/x-zip-compressed creator: mvalenti date_created: 2021-05-14T11:56:48Z date_updated: 2021-05-14T11:56:48Z file_id: '9391' file_name: Experimental_data.zip file_size: 99076111 relation: main_file file_date_updated: 2021-05-14T11:56:48Z fulldoi: https://doi.org/10.15479/AT:ISTA:9389 has_accepted_license: '1' oa: 1 oa_version: Published Version publisher: Institute of Science and Technology Austria related_material: record: - id: '8910' relation: used_in_publication status: public status: public title: Research data for "Non-topological zero bias peaks in full-shell nanowires induced by flux tunable Andreev states" tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '9403' abstract: - lang: eng text: Optimal decision making requires individuals to know their available options and to anticipate correctly what consequences these options have. In many social interactions, however, we refrain from gathering all relevant information, even if this information would help us make better decisions and is costless to obtain. This chapter examines several examples of “deliberate ignorance.” Two simple models are proposed to illustrate how ignorance can evolve among self-interested and payoff - maximizing individuals, and open problems are highlighted that lie ahead for future research to explore. article_processing_charge: No author: - first_name: Laura full_name: Schmid, Laura id: 38B437DE-F248-11E8-B48F-1D18A9856A87 last_name: Schmid orcid: 0000-0002-6978-7329 - first_name: Christian full_name: Hilbe, Christian last_name: Hilbe citation: ama: 'Schmid L, Hilbe C. The evolution of strategic ignorance in strategic interaction. In: Hertwig R, Engel C, eds. Deliberate Ignorance: Choosing Not To Know. Vol 29. Strüngmann Forum Reports. MIT Press; 2021:139-152.' apa: 'Schmid, L., & Hilbe, C. (2021). The evolution of strategic ignorance in strategic interaction. In R. Hertwig & C. Engel (Eds.), Deliberate Ignorance: Choosing Not To Know (Vol. 29, pp. 139–152). MIT Press.' chicago: 'Schmid, Laura, and Christian Hilbe. “The Evolution of Strategic Ignorance in Strategic Interaction.” In Deliberate Ignorance: Choosing Not To Know, edited by Ralph Hertwig and Christoph Engel, 29:139–52. Strüngmann Forum Reports. MIT Press, 2021.' ieee: 'L. Schmid and C. Hilbe, “The evolution of strategic ignorance in strategic interaction,” in Deliberate Ignorance: Choosing Not To Know, vol. 29, R. Hertwig and C. Engel, Eds. MIT Press, 2021, pp. 139–152.' ista: 'Schmid L, Hilbe C. 2021.The evolution of strategic ignorance in strategic interaction. In: Deliberate Ignorance: Choosing Not To Know. vol. 29, 139–152.' mla: 'Schmid, Laura, and Christian Hilbe. “The Evolution of Strategic Ignorance in Strategic Interaction.” Deliberate Ignorance: Choosing Not To Know, edited by Ralph Hertwig and Christoph Engel, vol. 29, MIT Press, 2021, pp. 139–52.' short: 'L. Schmid, C. Hilbe, in:, R. Hertwig, C. Engel (Eds.), Deliberate Ignorance: Choosing Not To Know, MIT Press, 2021, pp. 139–152.' date_created: 2021-05-19T12:25:42Z date_published: 2021-03-01T00:00:00Z date_updated: 2026-06-18T19:49:35Z day: '01' ddc: - '000' department: - _id: GradSch - _id: KrCh editor: - first_name: Ralph full_name: Hertwig, Ralph last_name: Hertwig - first_name: Christoph full_name: Engel, Christoph last_name: Engel intvolume: ' 29' language: - iso: eng main_file_link: - open_access: '1' url: https://esforum.de/publications/PDFs/sfr29/SFR29_09_Hilbe%20and%20Schmid.pdf month: '03' oa: 1 oa_version: Published Version page: 139-152 publication: 'Deliberate Ignorance: Choosing Not To Know' publication_identifier: isbn: - 978-0-262-04559-9 publisher: MIT Press quality_controlled: '1' series_title: Strüngmann Forum Reports status: public title: The evolution of strategic ignorance in strategic interaction type: book_chapter user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 29 year: '2021' ... --- _id: '9592' abstract: - lang: eng text: The convex grabbing game is a game where two players, Alice and Bob, alternate taking extremal points from the convex hull of a point set on the plane. Rational weights are given to the points. The goal of each player is to maximize the total weight over all points that they obtain. We restrict the setting to the case of binary weights. We show a construction of an arbitrarily large odd-sized point set that allows Bob to obtain almost 3/4 of the total weight. This construction answers a question asked by Matsumoto, Nakamigawa, and Sakuma in [Graphs and Combinatorics, 36/1 (2020)]. We also present an arbitrarily large even-sized point set where Bob can obtain the entirety of the total weight. Finally, we discuss conjectures about optimum moves in the convex grabbing game for both players in general. article_processing_charge: No arxiv: 1 author: - first_name: Martin full_name: Dvorak, Martin id: 40ED02A8-C8B4-11E9-A9C0-453BE6697425 last_name: Dvorak orcid: 0000-0001-5293-214X - first_name: Sara full_name: Nicholson, Sara last_name: Nicholson citation: ama: 'Dvorak M, Nicholson S. Massively winning configurations in the convex grabbing game on the plane. In: Proceedings of the 33rd Canadian Conference on Computational Geometry. Canadian Conference on Computational Geometry; 2021.' apa: 'Dvorak, M., & Nicholson, S. (2021). Massively winning configurations in the convex grabbing game on the plane. In Proceedings of the 33rd Canadian Conference on Computational Geometry. Halifax, NS, Canada; Virtual: Canadian Conference on Computational Geometry.' chicago: Dvorak, Martin, and Sara Nicholson. “Massively Winning Configurations in the Convex Grabbing Game on the Plane.” In Proceedings of the 33rd Canadian Conference on Computational Geometry. Canadian Conference on Computational Geometry, 2021. ieee: M. Dvorak and S. Nicholson, “Massively winning configurations in the convex grabbing game on the plane,” in Proceedings of the 33rd Canadian Conference on Computational Geometry, Halifax, NS, Canada; Virtual, 2021. ista: 'Dvorak M, Nicholson S. 2021. Massively winning configurations in the convex grabbing game on the plane. Proceedings of the 33rd Canadian Conference on Computational Geometry. CCCG: Canadian Conference on Computational Geometry.' mla: Dvorak, Martin, and Sara Nicholson. “Massively Winning Configurations in the Convex Grabbing Game on the Plane.” Proceedings of the 33rd Canadian Conference on Computational Geometry, Canadian Conference on Computational Geometry, 2021. short: M. Dvorak, S. Nicholson, in:, Proceedings of the 33rd Canadian Conference on Computational Geometry, Canadian Conference on Computational Geometry, 2021. conference: end_date: 2021-08-12 location: Halifax, NS, Canada; Virtual name: 'CCCG: Canadian Conference on Computational Geometry' start_date: 2021-08-10 date_created: 2021-06-22T15:57:11Z date_published: 2021-06-29T00:00:00Z date_updated: 2025-05-14T11:23:45Z day: '29' ddc: - '516' department: - _id: GradSch - _id: VlKo external_id: arxiv: - '2106.11247' file: - access_level: open_access checksum: 45accb1de9b7e0e4bb2fbfe5fd3e6239 content_type: application/pdf creator: mdvorak date_created: 2021-06-28T20:23:13Z date_updated: 2021-06-28T20:23:13Z file_id: '9616' file_name: Convex-Grabbing-Game_CCCG_proc_version.pdf file_size: 381306 relation: main_file success: 1 - access_level: open_access checksum: 9199cf18c65658553487458cc24d0ab2 content_type: application/pdf creator: kschuh date_created: 2021-08-12T10:57:21Z date_updated: 2021-08-12T10:57:21Z file_id: '9902' file_name: Convex-Grabbing-Game_FULL-VERSION.pdf file_size: 403645 relation: main_file success: 1 file_date_updated: 2021-08-12T10:57:21Z has_accepted_license: '1' keyword: - convex grabbing game - graph grabbing game - combinatorial game - convex geometry language: - iso: eng license: https://creativecommons.org/licenses/by-nd/4.0/ month: '06' oa: 1 oa_version: Published Version publication: Proceedings of the 33rd Canadian Conference on Computational Geometry publication_status: published publisher: Canadian Conference on Computational Geometry quality_controlled: '1' status: public title: Massively winning configurations in the convex grabbing game on the plane tmp: image: /image/cc_by_nd.png legal_code_url: https://creativecommons.org/licenses/by-nd/4.0/legalcode name: Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0) short: CC BY-ND (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '9818' abstract: - lang: eng text: Triangle mesh-based simulations are able to produce satisfying animations of knitted and woven cloth; however, they lack the rich geometric detail of yarn-level simulations. Naive texturing approaches do not consider yarn-level physics, while full yarn-level simulations may become prohibitively expensive for large garments. We propose a method to animate yarn-level cloth geometry on top of an underlying deforming mesh in a mechanics-aware fashion. Using triangle strains to interpolate precomputed yarn geometry, we are able to reproduce effects such as knit loops tightening under stretching. In combination with precomputed mesh animation or real-time mesh simulation, our method is able to animate yarn-level cloth in real-time at large scales. acknowledged_ssus: - _id: ScienComp acknowledgement: "We wish to thank the anonymous reviewers and the members of the Visual Computing Group at IST Austria for their valuable feedback. We also thank Seddi Labs for providing the garment model with fold-over seams.\r\nThis research was supported by the Scientific Service Units (SSU) of IST Austria through resources provided by Scientific\r\nComputing. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 638176. Rahul Narain is supported by a Pankaj Gupta Young Faculty Fellowship and a gift from Adobe Inc." article_number: '168' article_processing_charge: Yes (in subscription journal) article_type: original author: - first_name: Georg full_name: Sperl, Georg id: 4DD40360-F248-11E8-B48F-1D18A9856A87 last_name: Sperl - first_name: Rahul full_name: Narain, Rahul last_name: Narain - first_name: Christopher J full_name: Wojtan, Christopher J id: 3C61F1D2-F248-11E8-B48F-1D18A9856A87 last_name: Wojtan orcid: 0000-0001-6646-5546 citation: ama: Sperl G, Narain R, Wojtan C. Mechanics-aware deformation of yarn pattern geometry. ACM Transactions on Graphics. 2021;40(4). doi:10.1145/3450626.3459816 apa: Sperl, G., Narain, R., & Wojtan, C. (2021). Mechanics-aware deformation of yarn pattern geometry. ACM Transactions on Graphics. Association for Computing Machinery. https://doi.org/10.1145/3450626.3459816 chicago: Sperl, Georg, Rahul Narain, and Chris Wojtan. “Mechanics-Aware Deformation of Yarn Pattern Geometry.” ACM Transactions on Graphics. Association for Computing Machinery, 2021. https://doi.org/10.1145/3450626.3459816. ieee: G. Sperl, R. Narain, and C. Wojtan, “Mechanics-aware deformation of yarn pattern geometry,” ACM Transactions on Graphics, vol. 40, no. 4. Association for Computing Machinery, 2021. ista: Sperl G, Narain R, Wojtan C. 2021. Mechanics-aware deformation of yarn pattern geometry. ACM Transactions on Graphics. 40(4), 168. mla: Sperl, Georg, et al. “Mechanics-Aware Deformation of Yarn Pattern Geometry.” ACM Transactions on Graphics, vol. 40, no. 4, 168, Association for Computing Machinery, 2021, doi:10.1145/3450626.3459816. short: G. Sperl, R. Narain, C. Wojtan, ACM Transactions on Graphics 40 (2021). date_created: 2021-08-08T22:01:27Z date_published: 2021-08-01T00:00:00Z date_updated: 2026-06-18T19:57:47Z day: '01' ddc: - '000' department: - _id: GradSch - _id: ChWo doi: 10.1145/3450626.3459816 ec_funded: 1 external_id: isi: - '000674930900132' fulldoi: https://doi.org/10.1145/3450626.3459816 intvolume: ' 40' isi: 1 issue: '4' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1145/3450626.3459816 month: '08' oa: 1 oa_version: Published Version project: - _id: 2533E772-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '638176' name: 'Big Splash: Efficient Simulation of Natural Phenomena at Extremely Large Scales' publication: ACM Transactions on Graphics publication_identifier: eissn: - 1557-7368 issn: - 0730-0301 publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' related_material: link: - description: News on IST Webpage relation: press_release url: https://ist.ac.at/en/news/knitting-virtual-yarn/ record: - id: '9327' relation: software status: public - id: '12358' relation: dissertation_contains status: public scopus_import: '1' status: public title: Mechanics-aware deformation of yarn pattern geometry type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 40 year: '2021' ... --- OA_place: publisher OA_type: green _id: '6995' abstract: - lang: eng text: Human brain organoids represent a powerful tool for the study of human neurological diseases particularly those that impact brain growth and structure. However, many neurological diseases lack obvious anatomical abnormalities, yet significantly impact neural network functions, raising the question of whether organoids possess sufficient neural network architecture and complexity to model these conditions. Here, we explore the network level functions of brain organoids using calcium sensor imaging and extracellular recording approaches that together reveal the existence of complex oscillatory network behaviors reminiscent of intact brain preparations. We further demonstrate strikingly abnormal epileptiform network activity in organoids derived from a Rett Syndrome patient despite only modest anatomical differences from isogenically matched controls, and rescue with an unconventional neuromodulatory drug Pifithrin-α. Together, these findings provide an essential foundation for the utilization of human brain organoids to study intact and disordered human brain network formation and illustrate their utility in therapeutic discovery. acknowledgement: We thank S. Butler, T. Carmichael and members of the laboratory of B.G.N. for helpful discussions and comments on the manuscript; N. Vishlaghi and F. Turcios-Hernandez for technical assistance, and J. Lee, S.-K. Lee, H. Shinagawa and K. Yoshikawa for valuable reagents. We also thank the UCLA Eli and Edythe Broad Stem Cell Research Center (BSCRC) and Intellectual and Developmental Disabilities Research Center microscopy cores for access to imaging facilities. This work was supported by grants from the California Institute for Regenerative Medicine (CIRM) (DISC1-08819 to B.G.N.), the National Institute of Health (R01NS089817, R01DA051897 and P50HD103557 to B.G.N.; K08NS119747 to R.A.S.; K99HD096105 to M.W.; R01MH123922, R01MH121521 and P50HD103557 to M.J.G.; R01GM099134 to K.P.; R01NS103788 to W.E.L.; R01NS088571 to J.M.P.; R01NS030549 and R01AG050474 to I.M.), and research awards from the UCLA Jonsson Comprehensive Cancer Center and BSCRC Ablon Scholars Program (to B.G.N.), the BSCRC Innovation Program (to B.G.N., K.P. and W.E.L.), the UCLA BSCRC Steffy Brain Aging Research Fund (to B.G.N. and W.E.L.) and the UCLA Clinical and Translational Science Institute (to B.G.N.), Paul Allen Family Foundation Frontiers Group (to K.P. and W.E.L.), the March of Dimes Foundation (to W.E.L.) and the Simons Foundation Autism Research Initiative Bridge to Independence Program (to R.A.S. and M.J.G.). R.A.S. was also supported by the UCLA/NINDS Translational Neuroscience Training Grant (R25NS065723), a Research and Training Fellowship from the American Epilepsy Society, a Taking Flight Award from CURE Epilepsy and a Clinician Scientist training award from the UCLA BSCRC. J.E.B. was supported by the UCLA BSCRC Rose Hills Foundation Graduate Scholarship Training Program. M.W. was supported by postdoctoral training awards provided by the UCLA BSCRC and the Uehara Memorial Foundation. O.A.M. and A.K. were supported in part by the UCLA-California State University Northridge CIRM-Bridges training program (EDUC2-08411). We also acknowledge the support of the IDDRC Cells, Circuits and Systems Analysis, Microscopy and Genetics and Genomics Cores of the Semel Institute of Neuroscience at UCLA, which are supported by the NICHD (U54HD087101 and P50HD10355701). We lastly acknowledge support from a Quantitative and Computational Biosciences Collaboratory Postdoctoral Fellowship to S.M. and the Quantitative and Computational Biosciences Collaboratory community, directed by M. Pellegrini. article_processing_charge: No article_type: review author: - first_name: Ranmal A. full_name: Samarasinghe, Ranmal A. last_name: Samarasinghe - first_name: Osvaldo full_name: Miranda, Osvaldo id: 862A3C56-A8BF-11E9-B4FA-D9E3E5697425 last_name: Miranda orcid: 0000-0001-6618-6889 - first_name: Jessie E. full_name: Buth, Jessie E. last_name: Buth - first_name: Simon full_name: Mitchell, Simon last_name: Mitchell - first_name: Isabella full_name: Ferando, Isabella last_name: Ferando - first_name: Momoko full_name: Watanabe, Momoko last_name: Watanabe - first_name: Arinnae full_name: Kurdian, Arinnae last_name: Kurdian - first_name: Peyman full_name: Golshani, Peyman last_name: Golshani - first_name: Kathrin full_name: Plath, Kathrin last_name: Plath - first_name: William E. full_name: Lowry, William E. last_name: Lowry - first_name: Jack M. full_name: Parent, Jack M. last_name: Parent - first_name: Istvan full_name: Mody, Istvan last_name: Mody - first_name: Bennett G. full_name: Novitch, Bennett G. last_name: Novitch citation: ama: Samarasinghe RA, Miranda O, Buth JE, et al. Identification of neural oscillations and epileptiform changes in human brain organoids. Nature Neuroscience. 2021;24:32. doi:10.1038/s41593-021-00906-5 apa: Samarasinghe, R. A., Miranda, O., Buth, J. E., Mitchell, S., Ferando, I., Watanabe, M., … Novitch, B. G. (2021). Identification of neural oscillations and epileptiform changes in human brain organoids. Nature Neuroscience. Springer Nature. https://doi.org/10.1038/s41593-021-00906-5 chicago: Samarasinghe, Ranmal A., Osvaldo Miranda, Jessie E. Buth, Simon Mitchell, Isabella Ferando, Momoko Watanabe, Arinnae Kurdian, et al. “Identification of Neural Oscillations and Epileptiform Changes in Human Brain Organoids.” Nature Neuroscience. Springer Nature, 2021. https://doi.org/10.1038/s41593-021-00906-5. ieee: R. A. Samarasinghe et al., “Identification of neural oscillations and epileptiform changes in human brain organoids,” Nature Neuroscience, vol. 24. Springer Nature, p. 32, 2021. ista: Samarasinghe RA, Miranda O, Buth JE, Mitchell S, Ferando I, Watanabe M, Kurdian A, Golshani P, Plath K, Lowry WE, Parent JM, Mody I, Novitch BG. 2021. Identification of neural oscillations and epileptiform changes in human brain organoids. Nature Neuroscience. 24, 32. mla: Samarasinghe, Ranmal A., et al. “Identification of Neural Oscillations and Epileptiform Changes in Human Brain Organoids.” Nature Neuroscience, vol. 24, Springer Nature, 2021, p. 32, doi:10.1038/s41593-021-00906-5. short: R.A. Samarasinghe, O. Miranda, J.E. Buth, S. Mitchell, I. Ferando, M. Watanabe, A. Kurdian, P. Golshani, K. Plath, W.E. Lowry, J.M. Parent, I. Mody, B.G. Novitch, Nature Neuroscience 24 (2021) 32. date_created: 2019-11-10T11:23:58Z date_published: 2021-08-23T00:00:00Z date_updated: 2025-07-09T09:00:12Z day: '23' department: - _id: GradSch - _id: SiHi doi: 10.1038/s41593-021-00906-5 external_id: isi: - '000687516300001' pmid: - '34426698 ' fulldoi: https://doi.org/10.1038/s41593-021-00906-5 intvolume: ' 24' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1101/820183 month: '08' oa: 1 oa_version: Preprint page: '32' pmid: 1 publication: Nature Neuroscience publication_identifier: eissn: - 1546-1726 issn: - 1097-6256 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Identification of neural oscillations and epileptiform changes in human brain organoids type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 24 year: '2021' ... --- _id: '9891' abstract: - lang: eng text: 'Extending on ideas of Lewin, Lieb, and Seiringer [Phys. Rev. B 100, 035127 (2019)], we present a modified “floating crystal” trial state for jellium (also known as the classical homogeneous electron gas) with density equal to a characteristic function. This allows us to show that three definitions of the jellium energy coincide in dimensions d ≥ 2, thus extending the result of Cotar and Petrache [“Equality of the Jellium and uniform electron gas next-order asymptotic terms for Coulomb and Riesz potentials,” arXiv: 1707.07664 (2019)] and Lewin, Lieb, and Seiringer [Phys. Rev. B 100, 035127 (2019)] that the three definitions coincide in dimension d ≥ 3. We show that the jellium energy is also equivalent to a “renormalized energy” studied in a series of papers by Serfaty and others, and thus, by the work of Bétermin and Sandier [Constr. Approximation 47, 39–74 (2018)], we relate the jellium energy to the order n term in the logarithmic energy of n points on the unit 2-sphere. We improve upon known lower bounds for this renormalized energy. Additionally, we derive formulas for the jellium energy of periodic configurations.' acknowledgement: The author would like to thank Robert Seiringer for guidance and many helpful comments on this project. The author would also like to thank Mathieu Lewin for his comments on the manuscript and Lorenzo Portinale for providing his lecture notes for the course “Mathematics of quantum many-body systems” in spring 2020, taught by Robert Seiringer. The Proof of Theorem III.1 is inspired by these lecture notes. article_number: '083305' article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Asbjørn Bækgaard full_name: Lauritsen, Asbjørn Bækgaard id: e1a2682f-dc8d-11ea-abe3-81da9ac728f1 last_name: Lauritsen orcid: 0000-0003-4476-2288 citation: ama: Lauritsen AB. Floating Wigner crystal and periodic jellium configurations. Journal of Mathematical Physics. 2021;62(8). doi:10.1063/5.0053494 apa: Lauritsen, A. B. (2021). Floating Wigner crystal and periodic jellium configurations. Journal of Mathematical Physics. AIP Publishing. https://doi.org/10.1063/5.0053494 chicago: Lauritsen, Asbjørn Bækgaard. “Floating Wigner Crystal and Periodic Jellium Configurations.” Journal of Mathematical Physics. AIP Publishing, 2021. https://doi.org/10.1063/5.0053494. ieee: A. B. Lauritsen, “Floating Wigner crystal and periodic jellium configurations,” Journal of Mathematical Physics, vol. 62, no. 8. AIP Publishing, 2021. ista: Lauritsen AB. 2021. Floating Wigner crystal and periodic jellium configurations. Journal of Mathematical Physics. 62(8), 083305. mla: Lauritsen, Asbjørn Bækgaard. “Floating Wigner Crystal and Periodic Jellium Configurations.” Journal of Mathematical Physics, vol. 62, no. 8, 083305, AIP Publishing, 2021, doi:10.1063/5.0053494. short: A.B. Lauritsen, Journal of Mathematical Physics 62 (2021). corr_author: '1' date_created: 2021-08-12T07:08:36Z date_published: 2021-08-01T00:00:00Z date_updated: 2024-10-09T21:00:48Z day: '01' ddc: - '530' department: - _id: GradSch - _id: RoSe doi: 10.1063/5.0053494 external_id: arxiv: - '2103.07975' isi: - '000683960800003' file: - access_level: open_access checksum: d035be2b894c4d50d90ac5ce252e27cd content_type: application/pdf creator: cziletti date_created: 2021-10-27T12:57:06Z date_updated: 2021-10-27T12:57:06Z file_id: '10188' file_name: 2021_JMathPhy_Lauritsen.pdf file_size: 4352640 relation: main_file success: 1 file_date_updated: 2021-10-27T12:57:06Z fulldoi: https://doi.org/10.1063/5.0053494 has_accepted_license: '1' intvolume: ' 62' isi: 1 issue: '8' keyword: - Mathematical Physics - Statistical and Nonlinear Physics language: - iso: eng month: '08' oa: 1 oa_version: Published Version publication: Journal of Mathematical Physics publication_identifier: eissn: - 1089-7658 issn: - 0022-2488 publication_status: published publisher: AIP Publishing quality_controlled: '1' scopus_import: '1' status: public title: Floating Wigner crystal and periodic jellium configurations tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 62 year: '2021' ... --- _id: '9903' abstract: - lang: eng text: Eigenstate thermalization in quantum many-body systems implies that eigenstates at high energy are similar to random vectors. Identifying systems where at least some eigenstates are nonthermal is an outstanding question. In this Letter we show that interacting quantum models that have a nullspace—a degenerate subspace of eigenstates at zero energy (zero modes), which corresponds to infinite temperature, provide a route to nonthermal eigenstates. We analytically show the existence of a zero mode which can be represented as a matrix product state for a certain class of local Hamiltonians. In the more general case we use a subspace disentangling algorithm to generate an orthogonal basis of zero modes characterized by increasing entanglement entropy. We show evidence for an area-law entanglement scaling of the least-entangled zero mode in the broad parameter regime, leading to a conjecture that all local Hamiltonians with the nullspace feature zero modes with area-law entanglement scaling and, as such, break the strong thermalization hypothesis. Finally, we find zero modes in constrained models and propose a setup for observing their experimental signatures. acknowledgement: "We acknowledge useful discussions with V. Gritsev and A. Garkun and suggestions on implementation of the\r\nPPXPP model by D. Bluvstein. A. M. and M. S. were supported by the European Research Council (ERC) under\r\nthe European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 850899)" article_number: '060602' article_processing_charge: Yes (in subscription journal) article_type: letter_note arxiv: 1 author: - first_name: Volker full_name: Karle, Volker id: D7C012AE-D7ED-11E9-95E8-1EC5E5697425 last_name: Karle orcid: 0000-0002-6963-0129 - first_name: Maksym full_name: Serbyn, Maksym id: 47809E7E-F248-11E8-B48F-1D18A9856A87 last_name: Serbyn orcid: 0000-0002-2399-5827 - first_name: Alexios full_name: Michailidis, Alexios id: 36EBAD38-F248-11E8-B48F-1D18A9856A87 last_name: Michailidis orcid: 0000-0002-8443-1064 citation: ama: Karle V, Serbyn M, Michailidis A. Area-law entangled eigenstates from nullspaces of local Hamiltonians. Physical Review Letters. 2021;127(6). doi:10.1103/physrevlett.127.060602 apa: Karle, V., Serbyn, M., & Michailidis, A. (2021). Area-law entangled eigenstates from nullspaces of local Hamiltonians. Physical Review Letters. American Physical Society. https://doi.org/10.1103/physrevlett.127.060602 chicago: Karle, Volker, Maksym Serbyn, and Alexios Michailidis. “Area-Law Entangled Eigenstates from Nullspaces of Local Hamiltonians.” Physical Review Letters. American Physical Society, 2021. https://doi.org/10.1103/physrevlett.127.060602. ieee: V. Karle, M. Serbyn, and A. Michailidis, “Area-law entangled eigenstates from nullspaces of local Hamiltonians,” Physical Review Letters, vol. 127, no. 6. American Physical Society, 2021. ista: Karle V, Serbyn M, Michailidis A. 2021. Area-law entangled eigenstates from nullspaces of local Hamiltonians. Physical Review Letters. 127(6), 060602. mla: Karle, Volker, et al. “Area-Law Entangled Eigenstates from Nullspaces of Local Hamiltonians.” Physical Review Letters, vol. 127, no. 6, 060602, American Physical Society, 2021, doi:10.1103/physrevlett.127.060602. short: V. Karle, M. Serbyn, A. Michailidis, Physical Review Letters 127 (2021). date_created: 2021-08-13T09:27:39Z date_published: 2021-08-06T00:00:00Z date_updated: 2026-04-07T11:48:53Z day: '06' ddc: - '539' department: - _id: MaSe - _id: GradSch - _id: MiLe doi: 10.1103/physrevlett.127.060602 ec_funded: 1 external_id: arxiv: - '2102.13633' isi: - '000684276000002' file: - access_level: open_access checksum: 51218f302dcef99d90d1209809fcc874 content_type: application/pdf creator: mserbyn date_created: 2021-08-13T09:28:08Z date_updated: 2021-08-13T09:28:08Z file_id: '9904' file_name: PhysRevLett.127.060602_SOM.pdf file_size: 5064231 relation: main_file success: 1 file_date_updated: 2021-08-13T09:28:08Z fulldoi: https://doi.org/10.1103/physrevlett.127.060602 has_accepted_license: '1' intvolume: ' 127' isi: 1 issue: '6' language: - iso: eng month: '08' oa: 1 oa_version: Published Version project: - _id: 23841C26-32DE-11EA-91FC-C7463DDC885E call_identifier: H2020 grant_number: '850899' name: 'Non-Ergodic Quantum Matter: Universality, Dynamics and Control' publication: Physical Review Letters publication_identifier: eissn: - 1079-7114 issn: - 0031-9007 publication_status: published publisher: American Physical Society quality_controlled: '1' related_material: record: - id: '19393' relation: dissertation_contains status: public scopus_import: '1' status: public title: Area-law entangled eigenstates from nullspaces of local Hamiltonians tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 127 year: '2021' ... --- OA_place: publisher _id: '9920' abstract: - lang: eng text: 'This work is concerned with two fascinating circuit quantum electrodynamics components, the Josephson junction and the geometric superinductor, and the interesting experiments that can be done by combining the two. The Josephson junction has revolutionized the field of superconducting circuits as a non-linear dissipation-less circuit element and is used in almost all superconducting qubit implementations since the 90s. On the other hand, the superinductor is a relatively new circuit element introduced as a key component of the fluxonium qubit in 2009. This is an inductor with characteristic impedance larger than the resistance quantum and self-resonance frequency in the GHz regime. The combination of these two elements can occur in two fundamental ways: in parallel and in series. When connected in parallel the two create the fluxonium qubit, a loop with large inductance and a rich energy spectrum reliant on quantum tunneling. On the other hand placing the two elements in series aids with the measurement of the IV curve of a single Josephson junction in a high impedance environment. In this limit theory predicts that the junction will behave as its dual element: the phase-slip junction. While the Josephson junction acts as a non-linear inductor the phase-slip junction has the behavior of a non-linear capacitance and can be used to measure new Josephson junction phenomena, namely Coulomb blockade of Cooper pairs and phase-locked Bloch oscillations. The latter experiment allows for a direct link between frequency and current which is an elusive connection in quantum metrology. This work introduces the geometric superinductor, a superconducting circuit element where the high inductance is due to the geometry rather than the material properties of the superconductor, realized from a highly miniaturized superconducting planar coil. These structures will be described and characterized as resonators and qubit inductors and progress towards the measurement of phase-locked Bloch oscillations will be presented.' acknowledged_ssus: - _id: NanoFab - _id: M-Shop alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Matilda full_name: Peruzzo, Matilda id: 3F920B30-F248-11E8-B48F-1D18A9856A87 last_name: Peruzzo orcid: 0000-0002-3415-4628 citation: ama: Peruzzo M. Geometric superinductors and their applications in circuit quantum electrodynamics. 2021. doi:10.15479/at:ista:9920 apa: Peruzzo, M. (2021). Geometric superinductors and their applications in circuit quantum electrodynamics. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:9920 chicago: Peruzzo, Matilda. “Geometric Superinductors and Their Applications in Circuit Quantum Electrodynamics.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:9920. ieee: M. Peruzzo, “Geometric superinductors and their applications in circuit quantum electrodynamics,” Institute of Science and Technology Austria, 2021. ista: Peruzzo M. 2021. Geometric superinductors and their applications in circuit quantum electrodynamics. Institute of Science and Technology Austria. mla: Peruzzo, Matilda. Geometric Superinductors and Their Applications in Circuit Quantum Electrodynamics. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:9920. short: M. Peruzzo, Geometric Superinductors and Their Applications in Circuit Quantum Electrodynamics, Institute of Science and Technology Austria, 2021. corr_author: '1' date_created: 2021-08-16T09:44:09Z date_published: 2021-08-19T00:00:00Z date_updated: 2026-04-15T06:43:02Z day: '19' ddc: - '539' degree_awarded: PhD department: - _id: GradSch - _id: JoFi doi: 10.15479/at:ista:9920 file: - access_level: closed checksum: 3cd1986efde5121d7581f6fcf9090da8 content_type: application/x-zip-compressed creator: mperuzzo date_created: 2021-08-16T09:33:21Z date_updated: 2021-09-06T08:39:47Z file_id: '9924' file_name: GeometricSuperinductorsForCQED.zip file_size: 151387283 relation: source_file - access_level: open_access checksum: 50928c621cdf0775d7a5906b9dc8602c content_type: application/pdf creator: mperuzzo date_created: 2021-08-18T14:20:06Z date_updated: 2021-09-06T08:39:47Z file_id: '9939' file_name: GeometricSuperinductorsAndTheirApplicationsIncQED-1b.pdf file_size: 17596344 relation: main_file - access_level: closed checksum: 37f486aa1b622fe44af00d627ec13f6c content_type: application/pdf creator: mperuzzo date_created: 2021-08-18T14:20:09Z date_updated: 2021-09-06T08:39:47Z description: Extra copy of the thesis as PDF/A-2b file_id: '9940' file_name: GeometricSuperinductorsAndTheirApplicationsIncQED-2b.pdf file_size: 17592425 relation: other file_date_updated: 2021-09-06T08:39:47Z fulldoi: https://doi.org/10.15479/at:ista:9920 has_accepted_license: '1' keyword: - quantum computing - superinductor - quantum metrology language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: '149' publication_identifier: isbn: - 978-3-99078-013-8 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '9928' relation: part_of_dissertation status: public - id: '8755' relation: part_of_dissertation status: public status: public supervisor: - first_name: Johannes M full_name: Fink, Johannes M id: 4B591CBA-F248-11E8-B48F-1D18A9856A87 last_name: Fink orcid: 0000-0001-8112-028X title: Geometric superinductors and their applications in circuit quantum electrodynamics type: dissertation user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd year: '2021' ... --- _id: '9387' abstract: - lang: eng text: We report the complete analysis of a deterministic model of deleterious mutations and negative selection against them at two haploid loci without recombination. As long as mutation is a weaker force than selection, mutant alleles remain rare at the only stable equilibrium, and otherwise, a variety of dynamics are possible. If the mutation-free genotype is absent, generally the only stable equilibrium is the one that corresponds to fixation of the mutant allele at the locus where it is less deleterious. This result suggests that fixation of a deleterious allele that follows a click of the Muller’s ratchet is governed by natural selection, instead of random drift. acknowledgement: This work was supported by the Russian Science Foundation grant N 16-14-10173. article_number: '110729' article_processing_charge: No article_type: original author: - first_name: Kseniia full_name: Khudiakova, Kseniia id: 4E6DC800-AE37-11E9-AC72-31CAE5697425 last_name: Khudiakova orcid: 0000-0002-6246-1465 - first_name: Tatiana Yu. full_name: Neretina, Tatiana Yu. last_name: Neretina - first_name: Alexey S. full_name: Kondrashov, Alexey S. last_name: Kondrashov citation: ama: Khudiakova K, Neretina TY, Kondrashov AS. Two linked loci under mutation-selection balance and Muller’s ratchet. Journal of Theoretical Biology. 2021;524. doi:10.1016/j.jtbi.2021.110729 apa: Khudiakova, K., Neretina, T. Y., & Kondrashov, A. S. (2021). Two linked loci under mutation-selection balance and Muller’s ratchet. Journal of Theoretical Biology. Elsevier. https://doi.org/10.1016/j.jtbi.2021.110729 chicago: Khudiakova, Kseniia, Tatiana Yu. Neretina, and Alexey S. Kondrashov. “Two Linked Loci under Mutation-Selection Balance and Muller’s Ratchet.” Journal of Theoretical Biology. Elsevier, 2021. https://doi.org/10.1016/j.jtbi.2021.110729. ieee: K. Khudiakova, T. Y. Neretina, and A. S. Kondrashov, “Two linked loci under mutation-selection balance and Muller’s ratchet,” Journal of Theoretical Biology, vol. 524. Elsevier, 2021. ista: Khudiakova K, Neretina TY, Kondrashov AS. 2021. Two linked loci under mutation-selection balance and Muller’s ratchet. Journal of Theoretical Biology. 524, 110729. mla: Khudiakova, Kseniia, et al. “Two Linked Loci under Mutation-Selection Balance and Muller’s Ratchet.” Journal of Theoretical Biology, vol. 524, 110729, Elsevier, 2021, doi:10.1016/j.jtbi.2021.110729. short: K. Khudiakova, T.Y. Neretina, A.S. Kondrashov, Journal of Theoretical Biology 524 (2021). das_tickbox: '1' date_created: 2021-05-12T05:58:42Z date_published: 2021-04-24T00:00:00Z date_updated: 2026-07-06T12:58:31Z day: '24' department: - _id: GradSch doi: 10.1016/j.jtbi.2021.110729 external_id: isi: - '000659161500002' pmid: - '33901507' fulldoi: https://doi.org/10.1016/j.jtbi.2021.110729 intvolume: ' 524' isi: 1 keyword: - General Biochemistry - Genetics and Molecular Biology - Modelling and Simulation - Statistics and Probability - General Immunology and Microbiology - Applied Mathematics - General Agricultural and Biological Sciences - General Medicine language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/content/10.1101/477489v1 month: '04' oa: 1 oa_version: Preprint pmid: 1 publication: Journal of Theoretical Biology publication_identifier: issn: - 0022-5193 publication_status: published publisher: Elsevier quality_controlled: '1' scopus_import: '1' status: public title: Two linked loci under mutation-selection balance and Muller’s ratchet type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 524 year: '2021' ... --- OA_place: publisher _id: '9733' abstract: - lang: eng text: This thesis is the result of the research carried out by the author during his PhD at IST Austria between 2017 and 2021. It mainly focuses on the Fröhlich polaron model, specifically to its regime of strong coupling. This model, which is rigorously introduced and discussed in the introduction, has been of great interest in condensed matter physics and field theory for more than eighty years. It is used to describe an electron interacting with the atoms of a solid material (the strength of this interaction is modeled by the presence of a coupling constant α in the Hamiltonian of the system). The particular regime examined here, which is mathematically described by considering the limit α →∞, displays many interesting features related to the emergence of classical behavior, which allows for a simplified effective description of the system under analysis. The properties, the range of validity and a quantitative analysis of the precision of such classical approximations are the main object of the present work. We specify our investigation to the study of the ground state energy of the system, its dynamics and its effective mass. For each of these problems, we provide in the introduction an overview of the previously known results and a detailed account of the original contributions by the author. alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Dario full_name: Feliciangeli, Dario id: 41A639AA-F248-11E8-B48F-1D18A9856A87 last_name: Feliciangeli orcid: 0000-0003-0754-8530 citation: ama: Feliciangeli D. The polaron at strong coupling. 2021. doi:10.15479/at:ista:9733 apa: Feliciangeli, D. (2021). The polaron at strong coupling. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:9733 chicago: Feliciangeli, Dario. “The Polaron at Strong Coupling.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:9733. ieee: D. Feliciangeli, “The polaron at strong coupling,” Institute of Science and Technology Austria, 2021. ista: Feliciangeli D. 2021. The polaron at strong coupling. Institute of Science and Technology Austria. mla: Feliciangeli, Dario. The Polaron at Strong Coupling. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:9733. short: D. Feliciangeli, The Polaron at Strong Coupling, Institute of Science and Technology Austria, 2021. corr_author: '1' date_created: 2021-07-27T15:48:30Z date_published: 2021-08-20T00:00:00Z date_updated: 2026-07-06T14:02:25Z day: '20' ddc: - '515' - '519' - '539' degree_awarded: PhD department: - _id: GradSch - _id: RoSe - _id: JaMa doi: 10.15479/at:ista:9733 ec_funded: 1 file: - access_level: open_access checksum: e88bb8ca43948abe060eb2d2fa719881 content_type: application/pdf creator: dfelicia date_created: 2021-08-19T14:03:48Z date_updated: 2021-09-06T09:28:56Z file_id: '9944' file_name: Thesis_FeliciangeliA.pdf file_size: 1958710 relation: main_file - access_level: closed checksum: 72810843abee83705853505b3f8348aa content_type: application/octet-stream creator: dfelicia date_created: 2021-08-19T14:06:35Z date_updated: 2022-03-10T12:13:57Z file_id: '9945' file_name: thesis.7z file_size: 3771669 relation: source_file file_date_updated: 2022-03-10T12:13:57Z fulldoi: https://doi.org/10.15479/at:ista:9733 has_accepted_license: '1' language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: '180' project: - _id: 256E75B8-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '716117' name: Optimal Transport and Stochastic Dynamics - _id: 25C6DC12-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '694227' name: Analysis of quantum many-body systems - _id: fc31cba2-9c52-11eb-aca3-ff467d239cd2 grant_number: F6504 name: Taming Complexity in Partial Differential Systems publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '9787' relation: part_of_dissertation status: public - id: '9792' relation: part_of_dissertation status: public - id: '9791' relation: part_of_dissertation status: public - id: '9225' relation: part_of_dissertation status: public - id: '9781' relation: part_of_dissertation status: public status: public supervisor: - first_name: Robert full_name: Seiringer, Robert id: 4AFD0470-F248-11E8-B48F-1D18A9856A87 last_name: Seiringer orcid: 0000-0002-6781-0521 - first_name: Jan full_name: Maas, Jan id: 4C5696CE-F248-11E8-B48F-1D18A9856A87 last_name: Maas orcid: 0000-0002-0845-1338 title: The polaron at strong coupling tmp: image: /image/cc_by_nd.png legal_code_url: https://creativecommons.org/licenses/by-nd/4.0/legalcode name: Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0) short: CC BY-ND (4.0) type: dissertation user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd year: '2021' ... --- OA_place: repository OA_type: green _id: '10666' abstract: - lang: eng text: Adversarial training is an effective method to train deep learning models that are resilient to norm-bounded perturbations, with the cost of nominal performance drop. While adversarial training appears to enhance the robustness and safety of a deep model deployed in open-world decision-critical applications, counterintuitively, it induces undesired behaviors in robot learning settings. In this paper, we show theoretically and experimentally that neural controllers obtained via adversarial training are subjected to three types of defects, namely transient, systematic, and conditional errors. We first generalize adversarial training to a safety-domain optimization scheme allowing for more generic specifications. We then prove that such a learning process tends to cause certain error profiles. We support our theoretical results by a thorough experimental safety analysis in a robot-learning task. Our results suggest that adversarial training is not yet ready for robot learning. acknowledgement: M.L. and T.A.H. are supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). R.H. and D.R. are supported by Boeing and R.G. by Horizon-2020 ECSEL Project grant no. 783163 (iDev40). article_processing_charge: No arxiv: 1 author: - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Radu full_name: Grosu, Radu last_name: Grosu - first_name: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Lechner M, Hasani R, Grosu R, Rus D, Henzinger TA. Adversarial training is not ready for robot learning. In: 2021 IEEE International Conference on Robotics and Automation. IEEE; 2021:4140-4147. doi:10.1109/ICRA48506.2021.9561036' apa: 'Lechner, M., Hasani, R., Grosu, R., Rus, D., & Henzinger, T. A. (2021). Adversarial training is not ready for robot learning. In 2021 IEEE International Conference on Robotics and Automation (pp. 4140–4147). Xi’an, China: IEEE. https://doi.org/10.1109/ICRA48506.2021.9561036' chicago: Lechner, Mathias, Ramin Hasani, Radu Grosu, Daniela Rus, and Thomas A Henzinger. “Adversarial Training Is Not Ready for Robot Learning.” In 2021 IEEE International Conference on Robotics and Automation, 4140–47. IEEE, 2021. https://doi.org/10.1109/ICRA48506.2021.9561036. ieee: M. Lechner, R. Hasani, R. Grosu, D. Rus, and T. A. Henzinger, “Adversarial training is not ready for robot learning,” in 2021 IEEE International Conference on Robotics and Automation, Xi’an, China, 2021, pp. 4140–4147. ista: 'Lechner M, Hasani R, Grosu R, Rus D, Henzinger TA. 2021. Adversarial training is not ready for robot learning. 2021 IEEE International Conference on Robotics and Automation. ICRA: International Conference on Robotics and Automation, 4140–4147.' mla: Lechner, Mathias, et al. “Adversarial Training Is Not Ready for Robot Learning.” 2021 IEEE International Conference on Robotics and Automation, IEEE, 2021, pp. 4140–47, doi:10.1109/ICRA48506.2021.9561036. short: M. Lechner, R. Hasani, R. Grosu, D. Rus, T.A. Henzinger, in:, 2021 IEEE International Conference on Robotics and Automation, IEEE, 2021, pp. 4140–4147. conference: end_date: 2021-06-05 location: Xi'an, China name: 'ICRA: International Conference on Robotics and Automation' start_date: 2021-05-30 das_tickbox: '1' date_created: 2022-01-25T15:44:54Z date_published: 2021-06-01T00:00:00Z date_updated: 2026-07-07T06:20:35Z day: '01' ddc: - '000' department: - _id: GradSch - _id: ToHe doi: 10.1109/ICRA48506.2021.9561036 external_id: arxiv: - '2103.08187' isi: - '000765738803040' fulldoi: https://doi.org/10.1109/ICRA48506.2021.9561036 has_accepted_license: '1' isi: 1 language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/3.0/ main_file_link: - open_access: '1' url: https://arxiv.org/abs/2103.08187 month: '06' oa: 1 oa_version: Preprint page: 4140-4147 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: Formal methods for the design and analysis of complex systems publication: 2021 IEEE International Conference on Robotics and Automation publication_identifier: eisbn: - 978-1-7281-9077-8 eissn: - 2577-087X isbn: - 978-1-7281-9078-5 issn: - 1050-4729 publication_status: published publisher: IEEE quality_controlled: '1' related_material: record: - id: '11362' relation: dissertation_contains status: public scopus_import: '1' status: public title: Adversarial training is not ready for robot learning tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '10667' abstract: - lang: eng text: Bayesian neural networks (BNNs) place distributions over the weights of a neural network to model uncertainty in the data and the network's prediction. We consider the problem of verifying safety when running a Bayesian neural network policy in a feedback loop with infinite time horizon systems. Compared to the existing sampling-based approaches, which are inapplicable to the infinite time horizon setting, we train a separate deterministic neural network that serves as an infinite time horizon safety certificate. In particular, we show that the certificate network guarantees the safety of the system over a subset of the BNN weight posterior's support. Our method first computes a safe weight set and then alters the BNN's weight posterior to reject samples outside this set. Moreover, we show how to extend our approach to a safe-exploration reinforcement learning setting, in order to avoid unsafe trajectories during the training of the policy. We evaluate our approach on a series of reinforcement learning benchmarks, including non-Lyapunovian safety specifications. acknowledgement: This research was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award), ERC CoG 863818 (FoRM-SMArt), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. alternative_title: - ' Advances in Neural Information Processing Systems' article_processing_charge: No arxiv: 1 author: - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Ðorđe full_name: Žikelić, Ðorđe last_name: Žikelić - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Lechner M, Žikelić Ð, Chatterjee K, Henzinger TA. Infinite time horizon safety of Bayesian neural networks. In: 35th Conference on Neural Information Processing Systems. Neural Information Processing Systems Foundation; 2021. doi:10.48550/arXiv.2111.03165' apa: 'Lechner, M., Žikelić, Ð., Chatterjee, K., & Henzinger, T. A. (2021). Infinite time horizon safety of Bayesian neural networks. In 35th Conference on Neural Information Processing Systems. Virtual: Neural Information Processing Systems Foundation. https://doi.org/10.48550/arXiv.2111.03165' chicago: Lechner, Mathias, Ðorđe Žikelić, Krishnendu Chatterjee, and Thomas A Henzinger. “Infinite Time Horizon Safety of Bayesian Neural Networks.” In 35th Conference on Neural Information Processing Systems. Neural Information Processing Systems Foundation, 2021. https://doi.org/10.48550/arXiv.2111.03165. ieee: M. Lechner, Ð. Žikelić, K. Chatterjee, and T. A. Henzinger, “Infinite time horizon safety of Bayesian neural networks,” in 35th Conference on Neural Information Processing Systems, Virtual, 2021. ista: 'Lechner M, Žikelić Ð, Chatterjee K, Henzinger TA. 2021. Infinite time horizon safety of Bayesian neural networks. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, .' mla: Lechner, Mathias, et al. “Infinite Time Horizon Safety of Bayesian Neural Networks.” 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021, doi:10.48550/arXiv.2111.03165. short: M. Lechner, Ð. Žikelić, K. Chatterjee, T.A. Henzinger, in:, 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021. conference: end_date: 2021-12-10 location: Virtual name: 'NeurIPS: Neural Information Processing Systems' start_date: 2021-12-06 corr_author: '1' das_tickbox: '1' date_created: 2022-01-25T15:45:58Z date_published: 2021-12-01T00:00:00Z date_updated: 2026-07-07T06:49:10Z day: '01' ddc: - '000' department: - _id: GradSch - _id: ToHe - _id: KrCh doi: 10.48550/arXiv.2111.03165 ec_funded: 1 external_id: arxiv: - '2111.03165' file: - access_level: open_access checksum: 0fc0f852525c10dda9cc9ffea07fb4e4 content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:39:59Z date_updated: 2022-01-26T07:39:59Z file_id: '10682' file_name: infinite_time_horizon_safety_o.pdf file_size: 452492 relation: main_file success: 1 file_date_updated: 2022-01-26T07:39:59Z fulldoi: https://doi.org/10.48550/arXiv.2111.03165 has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://proceedings.neurips.cc/paper/2021/hash/544defa9fddff50c53b71c43e0da72be-Abstract.html month: '12' oa: 1 oa_version: Published Version project: - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: Formal methods for the design and analysis of complex systems publication: 35th Conference on Neural Information Processing Systems publication_identifier: issn: - 1049-5258 publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' related_material: record: - id: '11362' relation: dissertation_contains status: public status: public title: Infinite time horizon safety of Bayesian neural networks tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '10670' abstract: - lang: eng text: "Imitation learning enables high-fidelity, vision-based learning of policies within rich, photorealistic environments. However, such techniques often rely on traditional discrete-time neural models and face difficulties in generalizing to domain shifts by failing to account for the causal relationships between the agent and the environment. In this paper, we propose a theoretical and experimental framework for learning causal representations using continuous-time neural networks, specifically over their discrete-time counterparts. We evaluate our method in the context of visual-control learning of drones over a series of complex tasks, ranging from short- and long-term navigation, to chasing static and dynamic objects through photorealistic environments. Our results demonstrate that causal continuous-time\r\ndeep models can perform robust navigation tasks, where advanced recurrent models fail. These models learn complex causal control representations directly from raw visual inputs and scale to solve a variety of tasks using imitation learning." acknowledgement: "C.V., R.H. A.A. and D.R. are partially supported by Boeing and MIT. A.A. is supported by the National Science Foundation (NSF) Graduate Research Fellowship Program. M.L. is supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). Research was sponsored by the United States Air Force Research Laboratory and the United States Air Force Artificial Intelligence Accelerator and was accomplished under Cooperative Agreement Number FA8750-19-2-1000. The views and conclusions contained in this document are those of the authors\r\nand should not be interpreted as representing the official policies, either expressed or implied, of the United States Air Force or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.\r\n" alternative_title: - ' Advances in Neural Information Processing Systems' article_processing_charge: No arxiv: 1 author: - first_name: Charles J full_name: Vorbach, Charles J last_name: Vorbach - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Alexander full_name: Amini, Alexander last_name: Amini - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Daniela full_name: Rus, Daniela last_name: Rus citation: ama: 'Vorbach CJ, Hasani R, Amini A, Lechner M, Rus D. Causal navigation by continuous-time neural networks. In: 35th Conference on Neural Information Processing Systems. Neural Information Processing Systems Foundation; 2021.' apa: 'Vorbach, C. J., Hasani, R., Amini, A., Lechner, M., & Rus, D. (2021). Causal navigation by continuous-time neural networks. In 35th Conference on Neural Information Processing Systems. Virtual: Neural Information Processing Systems Foundation.' chicago: Vorbach, Charles J, Ramin Hasani, Alexander Amini, Mathias Lechner, and Daniela Rus. “Causal Navigation by Continuous-Time Neural Networks.” In 35th Conference on Neural Information Processing Systems. Neural Information Processing Systems Foundation, 2021. ieee: C. J. Vorbach, R. Hasani, A. Amini, M. Lechner, and D. Rus, “Causal navigation by continuous-time neural networks,” in 35th Conference on Neural Information Processing Systems, Virtual, 2021. ista: 'Vorbach CJ, Hasani R, Amini A, Lechner M, Rus D. 2021. Causal navigation by continuous-time neural networks. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, .' mla: Vorbach, Charles J., et al. “Causal Navigation by Continuous-Time Neural Networks.” 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021. short: C.J. Vorbach, R. Hasani, A. Amini, M. Lechner, D. Rus, in:, 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021. conference: end_date: 2021-12-10 location: Virtual name: 'NeurIPS: Neural Information Processing Systems' start_date: 2021-12-06 das_tickbox: '1' date_created: 2022-01-25T15:47:50Z date_published: 2021-12-01T00:00:00Z date_updated: 2026-07-07T06:49:46Z day: '01' ddc: - '000' department: - _id: GradSch - _id: ToHe external_id: arxiv: - '2106.08314' file: - access_level: open_access checksum: be81f0ade174a8c9b2d4fe09590b2021 content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:37:24Z date_updated: 2022-01-26T07:37:24Z file_id: '10679' file_name: NeurIPS-2021-causal-navigation-by-continuous-time-neural-networks-Paper.pdf file_size: 6841228 relation: main_file success: 1 file_date_updated: 2022-01-26T07:37:24Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://proceedings.neurips.cc/paper/2021/hash/67ba02d73c54f0b83c05507b7fb7267f-Abstract.html month: '12' oa: 1 oa_version: Published Version project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: Formal methods for the design and analysis of complex systems publication: 35th Conference on Neural Information Processing Systems publication_identifier: issn: - 1049-5258 publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' status: public title: Causal navigation by continuous-time neural networks tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '10080' abstract: - lang: eng text: Hippocampal and neocortical neural activity is modulated by the position of the individual in space. While hippocampal neurons provide the basis for a spatial map, prefrontal cortical neurons generalize over environmental features. Whether these generalized representations result from a bidirectional interaction with, or are mainly derived from hippocampal spatial representations is not known. By examining simultaneously recorded hippocampal and medial prefrontal neurons, we observed that prefrontal spatial representations show a delayed coherence with hippocampal ones. We also identified subpopulations of cells in the hippocampus and medial prefrontal cortex that formed functional cross-area couplings; these resembled the optimal connections predicted by a probabilistic model of spatial information transfer and generalization. Moreover, cross-area couplings were strongest and had the shortest delay preceding spatial decision-making. Our results suggest that generalized spatial coding in the medial prefrontal cortex is inherited from spatial representations in the hippocampus, and that the routing of information can change dynamically with behavioral demands. acknowledgement: We thank Federico Stella for invaluable suggestions and discussions. We thank Yosman BapatDhar and Andrea Cumpelik for comments, help and suggestions on the exposure of the text. We thank Predrag Živadinović and Juliana Couras for comments on the text and the figures. This work was supported by the EU-FP7 MC-ITN IN-SENS (grant 607616). article_processing_charge: No author: - first_name: Michele full_name: Nardin, Michele id: 30BD0376-F248-11E8-B48F-1D18A9856A87 last_name: Nardin orcid: 0000-0001-8849-6570 - first_name: Karola full_name: Käfer, Karola id: 2DAA49AA-F248-11E8-B48F-1D18A9856A87 last_name: Käfer - first_name: Jozsef L full_name: Csicsvari, Jozsef L id: 3FA14672-F248-11E8-B48F-1D18A9856A87 last_name: Csicsvari orcid: 0000-0002-5193-4036 biorxivid: 1 citation: ama: Nardin M, Käfer K, Csicsvari JL. The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus. bioRxiv. doi:10.1101/2021.09.30.462269 apa: Nardin, M., Käfer, K., & Csicsvari, J. L. (n.d.). The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus. bioRxiv. https://doi.org/10.1101/2021.09.30.462269 chicago: Nardin, Michele, Karola Käfer, and Jozsef L Csicsvari. “The Generalized Spatial Representation in the Prefrontal Cortex Is Inherited from the Hippocampus.” BioRxiv, n.d. https://doi.org/10.1101/2021.09.30.462269. ieee: M. Nardin, K. Käfer, and J. L. Csicsvari, “The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus,” bioRxiv. . ista: Nardin M, Käfer K, Csicsvari JL. The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus. bioRxiv, 10.1101/2021.09.30.462269. mla: Nardin, Michele, et al. “The Generalized Spatial Representation in the Prefrontal Cortex Is Inherited from the Hippocampus.” BioRxiv, doi:10.1101/2021.09.30.462269. short: M. Nardin, K. Käfer, J.L. Csicsvari, BioRxiv (n.d.). das_tickbox: '1' date_created: 2021-10-04T06:28:32Z date_published: 2021-10-02T00:00:00Z date_updated: 2026-07-29T06:33:53Z day: '02' department: - _id: GradSch - _id: JoCs doi: 10.1101/2021.09.30.462269 ec_funded: 1 external_id: biorxivid: - 10.1101/2021.09.30.462269 fulldoi: https://doi.org/10.1101/2021.09.30.462269 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1101/2021.09.30.462269 month: '10' oa: 1 oa_version: Preprint project: - _id: 257BBB4C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '607616' name: inter-and intracellular signalling in schizophrenia publication: bioRxiv publication_status: submitted status: public title: The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- OA_place: publisher _id: '9418' abstract: - lang: eng text: "Deep learning is best known for its empirical success across a wide range of applications\r\nspanning computer vision, natural language processing and speech. Of equal significance,\r\nthough perhaps less known, are its ramifications for learning theory: deep networks have\r\nbeen observed to perform surprisingly well in the high-capacity regime, aka the overfitting\r\nor underspecified regime. Classically, this regime on the far right of the bias-variance curve\r\nis associated with poor generalisation; however, recent experiments with deep networks\r\nchallenge this view.\r\n\r\nThis thesis is devoted to investigating various aspects of underspecification in deep learning.\r\nFirst, we argue that deep learning models are underspecified on two levels: a) any given\r\ntraining dataset can be fit by many different functions, and b) any given function can be\r\nexpressed by many different parameter configurations. We refer to the second kind of\r\nunderspecification as parameterisation redundancy and we precisely characterise its extent.\r\nSecond, we characterise the implicit criteria (the inductive bias) that guide learning in the\r\nunderspecified regime. Specifically, we consider a nonlinear but tractable classification\r\nsetting, and show that given the choice, neural networks learn classifiers with a large margin.\r\nThird, we consider learning scenarios where the inductive bias is not by itself sufficient to\r\ndeal with underspecification. We then study different ways of ‘tightening the specification’: i)\r\nIn the setting of representation learning with variational autoencoders, we propose a hand-\r\ncrafted regulariser based on mutual information. ii) In the setting of binary classification, we\r\nconsider soft-label (real-valued) supervision. We derive a generalisation bound for linear\r\nnetworks supervised in this way and verify that soft labels facilitate fast learning. Finally, we\r\nexplore an application of soft-label supervision to the training of multi-exit models." acknowledged_ssus: - _id: ScienComp - _id: CampIT - _id: E-Lib alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Phuong full_name: Bui Thi Mai, Phuong id: 3EC6EE64-F248-11E8-B48F-1D18A9856A87 last_name: Bui Thi Mai citation: ama: Phuong M. Underspecification in deep learning. 2021. doi:10.15479/AT:ISTA:9418 apa: Phuong, M. (2021). Underspecification in deep learning. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:9418 chicago: Phuong, Mary. “Underspecification in Deep Learning.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/AT:ISTA:9418. ieee: M. Phuong, “Underspecification in deep learning,” Institute of Science and Technology Austria, 2021. ista: Phuong M. 2021. Underspecification in deep learning. Institute of Science and Technology Austria. mla: Phuong, Mary. Underspecification in Deep Learning. Institute of Science and Technology Austria, 2021, doi:10.15479/AT:ISTA:9418. short: M. Phuong, Underspecification in Deep Learning, Institute of Science and Technology Austria, 2021. corr_author: '1' date_created: 2021-05-24T13:06:23Z date_published: 2021-05-30T00:00:00Z date_updated: 2026-07-30T05:33:52Z day: '30' ddc: - '000' degree_awarded: PhD department: - _id: GradSch - _id: ChLa doi: 10.15479/AT:ISTA:9418 doi_confirm: '1' file: - access_level: open_access checksum: 4f0abe64114cfed264f9d36e8d1197e3 content_type: application/pdf creator: bphuong date_created: 2021-05-24T11:22:29Z date_updated: 2021-05-24T11:22:29Z file_id: '9419' file_name: mph-thesis-v519-pdfimages.pdf file_size: 2673905 relation: main_file success: 1 - access_level: closed checksum: f5699e876bc770a9b0df8345a77720a2 content_type: application/zip creator: bphuong date_created: 2021-05-24T11:56:02Z date_updated: 2021-05-24T11:56:02Z file_id: '9420' file_name: thesis.zip file_size: 92995100 relation: source_file file_date_updated: 2021-05-24T11:56:02Z fulldoi: https://doi.org/10.15479/AT:ISTA:9418 has_accepted_license: '1' language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: '125' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '7435' relation: part_of_dissertation status: deleted - id: '7481' relation: part_of_dissertation status: public - id: '9416' relation: part_of_dissertation status: public - id: '7479' relation: part_of_dissertation status: public status: public supervisor: - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 title: Underspecification in deep learning type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2021' ... --- _id: '9416' abstract: - lang: eng text: 'We study the inductive bias of two-layer ReLU networks trained by gradient flow. We identify a class of easy-to-learn (`orthogonally separable'') datasets, and characterise the solution that ReLU networks trained on such datasets converge to. Irrespective of network width, the solution turns out to be a combination of two max-margin classifiers: one corresponding to the positive data subset and one corresponding to the negative data subset. The proof is based on the recently introduced concept of extremal sectors, for which we prove a number of properties in the context of orthogonal separability. In particular, we prove stationarity of activation patterns from some time onwards, which enables a reduction of the ReLU network to an ensemble of linear subnetworks.' article_processing_charge: No author: - first_name: Phuong full_name: Bui Thi Mai, Phuong id: 3EC6EE64-F248-11E8-B48F-1D18A9856A87 last_name: Bui Thi Mai - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 citation: ama: 'Phuong M, Lampert C. The inductive bias of ReLU networks on orthogonally separable data. In: 9th International Conference on Learning Representations. ; 2021.' apa: Phuong, M., & Lampert, C. (2021). The inductive bias of ReLU networks on orthogonally separable data. In 9th International Conference on Learning Representations. Virtual. chicago: Phuong, Mary, and Christoph Lampert. “The Inductive Bias of ReLU Networks on Orthogonally Separable Data.” In 9th International Conference on Learning Representations, 2021. ieee: M. Phuong and C. Lampert, “The inductive bias of ReLU networks on orthogonally separable data,” in 9th International Conference on Learning Representations, Virtual, 2021. ista: 'Phuong M, Lampert C. 2021. The inductive bias of ReLU networks on orthogonally separable data. 9th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.' mla: Phuong, Mary, and Christoph Lampert. “The Inductive Bias of ReLU Networks on Orthogonally Separable Data.” 9th International Conference on Learning Representations, 2021. short: M. Phuong, C. Lampert, in:, 9th International Conference on Learning Representations, 2021. conference: end_date: 2021-05-07 location: Virtual name: 'ICLR: International Conference on Learning Representations' start_date: 2021-05-03 corr_author: '1' date_created: 2021-05-24T11:16:46Z date_published: 2021-05-01T00:00:00Z date_updated: 2026-07-30T05:33:51Z day: '01' ddc: - '000' department: - _id: GradSch - _id: ChLa file: - access_level: open_access checksum: f34ff17017527db5ba6927f817bdd125 content_type: application/pdf creator: bphuong date_created: 2021-05-24T11:15:57Z date_updated: 2021-05-24T11:15:57Z file_id: '9417' file_name: iclr2021_conference.pdf file_size: 502356 relation: main_file file_date_updated: 2021-05-24T11:15:57Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://openreview.net/pdf?id=krz7T0xU9Z_ month: '05' oa: 1 oa_version: Published Version publication: 9th International Conference on Learning Representations publication_status: published quality_controlled: '1' related_material: record: - id: '9418' relation: dissertation_contains status: public scopus_import: '1' status: public title: The inductive bias of ReLU networks on orthogonally separable data type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '9356' abstract: - lang: eng text: 'In runtime verification, a monitor watches a trace of a system and, if possible, decides after observing each finite prefix whether or not the unknown infinite trace satisfies a given specification. We generalize the theory of runtime verification to monitors that attempt to estimate numerical values of quantitative trace properties (instead of attempting to conclude boolean values of trace specifications), such as maximal or average response time along a trace. Quantitative monitors are approximate: with every finite prefix, they can improve their estimate of the infinite trace''s unknown property value. Consequently, quantitative monitors can be compared with regard to a precision-cost trade-off: better approximations of the property value require more monitor resources, such as states (in the case of finite-state monitors) or registers, and additional resources yield better approximations. We introduce a formal framework for quantitative and approximate monitoring, show how it conservatively generalizes the classical boolean setting for monitoring, and give several precision-cost trade-offs for monitors. For example, we prove that there are quantitative properties for which every additional register improves monitoring precision.' acknowledgement: We thank the anonymous reviewers for their helpful comments. This research was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). article_number: '9470547' article_processing_charge: No arxiv: 1 author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Naci E full_name: Sarac, Naci E id: 8C6B42F8-C8E6-11E9-A03A-F2DCE5697425 last_name: Sarac citation: ama: 'Henzinger TA, Sarac NE. Quantitative and approximate monitoring. In: Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science. IEEE; 2021. doi:10.1109/LICS52264.2021.9470547' apa: 'Henzinger, T. A., & Sarac, N. E. (2021). Quantitative and approximate monitoring. In Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science. Online: IEEE. https://doi.org/10.1109/LICS52264.2021.9470547' chicago: Henzinger, Thomas A, and Naci E Sarac. “Quantitative and Approximate Monitoring.” In Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science. IEEE, 2021. https://doi.org/10.1109/LICS52264.2021.9470547. ieee: T. A. Henzinger and N. E. Sarac, “Quantitative and approximate monitoring,” in Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, Online, 2021. ista: 'Henzinger TA, Sarac NE. 2021. Quantitative and approximate monitoring. Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science. LICS: Logic in Computer Science, 9470547.' mla: Henzinger, Thomas A., and Naci E. Sarac. “Quantitative and Approximate Monitoring.” Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, 9470547, IEEE, 2021, doi:10.1109/LICS52264.2021.9470547. short: T.A. Henzinger, N.E. Sarac, in:, Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, IEEE, 2021. conference: end_date: 2021-07-02 location: Online name: 'LICS: Logic in Computer Science' start_date: 2021-06-29 date_created: 2021-04-30T17:30:47Z date_published: 2021-06-29T00:00:00Z date_updated: 2026-08-12T06:39:11Z day: '29' ddc: - '000' department: - _id: GradSch - _id: ToHe doi: 10.1109/LICS52264.2021.9470547 external_id: arxiv: - '2105.08353' isi: - '000947350400021' file: - access_level: open_access checksum: 6e4cba3f72775f479c5b1b75d1a4a0c4 content_type: application/pdf creator: esarac date_created: 2021-06-16T08:23:54Z date_updated: 2021-06-16T08:23:54Z file_id: '9557' file_name: qam.pdf file_size: 641990 relation: main_file success: 1 file_date_updated: 2021-06-16T08:23:54Z fulldoi: https://doi.org/10.1109/LICS52264.2021.9470547 has_accepted_license: '1' isi: 1 language: - iso: eng month: '06' oa: 1 oa_version: Published Version project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: Formal methods for the design and analysis of complex systems publication: Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science publication_status: published publisher: IEEE quality_controlled: '1' related_material: record: - id: '20147' relation: dissertation_contains status: public scopus_import: '1' status: public title: Quantitative and approximate monitoring type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ...