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11357 Publications


2021 | Published | Conference Paper | IST-REx-ID: 14177 | OA
Träuble, Frederik, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, and Stefan Bauer. “On Disentangled Representations Learned from Correlated Data.” In Proceedings of the 38th International Conference on Machine Learning, 139:10401–12. ML Research Press, 2021.
[Published Version] View | Download Published Version (ext.) | arXiv
 

2021 | Published | Conference Paper | IST-REx-ID: 14178 | OA
Dittadi, Andrea, Frederik Träuble, Francesco Locatello, Manuel Wüthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, and Bernhard Schölkopf. “On the Transfer of Disentangled Representations in Realistic Settings.” In The Ninth International Conference on Learning Representations, 2021.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2021 | Published | Conference Paper | IST-REx-ID: 14179 | OA
Kügelgen, Julius von, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, and Francesco Locatello. “Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style.” In Advances in Neural Information Processing Systems, 34:16451–67, 2021.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2021 | Published | Conference Paper | IST-REx-ID: 14180 | OA
Rahaman, Nasim, Muhammad Waleed Gondal, Shruti Joshi, Peter Gehler, Yoshua Bengio, Francesco Locatello, and Bernhard Schölkopf. “Dynamic Inference with Neural Interpreters.” In Advances in Neural Information Processing Systems, 34:10985–98, 2021.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2021 | Published | Conference Paper | IST-REx-ID: 14181 | OA
Dresdner, Gideon, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, and Gunnar Rätsch. “Boosting Variational Inference with Locally Adaptive Step-Sizes.” In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2337–43. International Joint Conferences on Artificial Intelligence, 2021. https://doi.org/10.24963/ijcai.2021/322.
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2021 | Published | Conference Paper | IST-REx-ID: 14182 | OA
Träuble, Frederik, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, and Peter Gehler. “Backward-Compatible Prediction Updates: A Probabilistic Approach.” In 35th Conference on Neural Information Processing Systems, 34:116–28, 2021.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2021 | Patent | IST-REx-ID: 14185 | OA
Weissenborn, Dirk, Jakob Uszkoreit, Thomas Unterthiner, Aravindh Mahendran, Francesco Locatello, Thomas Kipf, Georg Heigold, and Alexey Dosovitskiy. “Object-Centric Learning with Slot Attention,” 2021.
[Published Version] View | Download Published Version (ext.) | arXiv
 

2021 | Submitted | Preprint | IST-REx-ID: 14221 | OA
Locatello, Francesco. “Enforcing and Discovering Structure in Machine Learning.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2111.13693.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2021 | Published | Conference Paper | IST-REx-ID: 14332
Träuble, Frederik, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, and Stefan Bauer. “Representation Learning for Out-of-Distribution Generalization in Reinforcement Learning.” In ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021.
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2021 | Published | Journal Article | IST-REx-ID: 17876
Fu, Tianren, Kathleen Frommer, Colin Nuckolls, and Latha Venkataraman. “Single-Molecule Junction Formation in Break-Junction Measurements.” The Journal of Physical Chemistry Letters. American Chemical Society, 2021. https://doi.org/10.1021/acs.jpclett.1c03160.
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2021 | Published | Journal Article | IST-REx-ID: 17877
Stone, Ilana, Rachel L. Starr, Yaping Zang, Colin Nuckolls, Michael L. Steigerwald, Tristan H. Lambert, Xavier Roy, and Latha Venkataraman. “A Single-Molecule Blueprint for Synthesis.” Nature Reviews Chemistry. Springer Nature, 2021. https://doi.org/10.1038/s41570-021-00316-y.
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2021 | Published | Journal Article | IST-REx-ID: 17899 | OA
Zhang, Boyuan, Marc H. Garner, Liang Li, Luis M. Campos, Gemma C. Solomon, and Latha Venkataraman. “Destructive Quantum Interference in Heterocyclic Alkanes: The Search for Ultra-Short Molecular Insulators.” Chemical Science. Royal Society of Chemistry, 2021. https://doi.org/10.1039/d1sc02287c.
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2021 | Published | Journal Article | IST-REx-ID: 17900
Greenwald, Julia E., Joseph Cameron, Neil J. Findlay, Tianren Fu, Suman Gunasekaran, Peter J. Skabara, and Latha Venkataraman. “Highly Nonlinear Transport across Single-Molecule Junctions via Destructive Quantum Interference.” Nature Nanotechnology. Springer Nature, 2021. https://doi.org/10.1038/s41565-020-00807-x.
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2021 | Published | Journal Article | IST-REx-ID: 17901
Medina Rivero, Samara, Paloma García Arroyo, Liang Li, Suman Gunasekaran, Thijs Stuyver, María José Mancheño, Mercedes Alonso, Latha Venkataraman, José L. Segura, and Juan Casado. “Single-Molecule Conductance in a Unique Cross-Conjugated Tetra(Aminoaryl)Ethene.” Chemical Communications. Royal Society of Chemistry, 2021. https://doi.org/10.1039/d0cc07124b.
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2021 | Published | Journal Article | IST-REx-ID: 18192 | OA
Bohrdt, A., S. Kim, A. Lukin, M. Rispoli, R. Schittko, M. Knap, M. Greiner, and Julian Leonard. “Analyzing Nonequilibrium Quantum States through Snapshots with Artificial Neural Networks.” Physical Review Letters. American Physical Society, 2021. https://doi.org/10.1103/physrevlett.127.150504.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2021 | Published | Journal Article | IST-REx-ID: 18193 | OA
Palm, F. A., M. Buser, Julian Leonard, M. Aidelsburger, U. Schollwöck, and F. Grusdt. “Bosonic Pfaffian State in the Hofstadter-Bose-Hubbard Model.” Physical Review B. American Physical Society, 2021. https://doi.org/10.1103/physrevb.103.l161101.
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2021 | Published | Journal Article | IST-REx-ID: 18233 | OA
Nahshan, Yury, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, and Avi Mendelson. “Loss Aware Post-Training Quantization.” Machine Learning. Springer Nature, 2021. https://doi.org/10.1007/s10994-021-06053-z.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2021 | Published | Journal Article | IST-REx-ID: 18234
Baskin, Chaim, Evgenii Zheltonozhkii, Tal Rozen, Natan Liss, Yoav Chai, Eli Schwartz, Raja Giryes, Alex M. Bronstein, and Avi Mendelson. “NICE: Noise Injection and Clamping Estimation for Neural Network Quantization.” Mathematics. MDPI, 2021. https://doi.org/10.3390/math9172144.
[Published Version] View | DOI | arXiv
 

2021 | Published | Journal Article | IST-REx-ID: 18235 | OA
Doveh, Sivan, Eli Schwartz, Chao Xue, Rogerio Feris, Alex M. Bronstein, Raja Giryes, and Leonid Karlinsky. “MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification.” Pattern Recognition Letters. Elsevier, 2021. https://doi.org/10.1016/j.patrec.2021.05.010.
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2021 | Published | Journal Article | IST-REx-ID: 18236
Elul, Yonatan, Aviv A. Rosenberg, Assaf Schuster, Alex M. Bronstein, and Yael Yaniv. “Meeting the Unmet Needs of Clinicians from AI Systems Showcased for Cardiology with Deep-Learning–Based ECG Analysis.” Proceedings of the National Academy of Sciences. National Academy of Sciences, 2021. https://doi.org/10.1073/pnas.2020620118.
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