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707 Publications


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.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 

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.
[Published Version] View | DOI | Download Published Version (ext.) | PubMed | Europe PMC
 

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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

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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2021 | Published | Journal Article | IST-REx-ID: 18237 | OA
Baskin, Chaim, Natan Liss, Eli Schwartz, Evgenii Zheltonozhskii, Raja Giryes, Alex M. Bronstein, and Avi Mendelson. “UNIQ: Uniform Noise Injection for Non-Uniform Quantization of Neural Networks.” ACM Transactions on Computer Systems. Association for Computing Machinery, 2021. https://doi.org/10.1145/3444943.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2021 | Published | Journal Article | IST-REx-ID: 18238 | OA
Karbachevsky, Alex, Chaim Baskin, Evgenii Zheltonozhskii, Yevgeny Yermolin, Freddy Gabbay, Alex M. Bronstein, and Avi Mendelson. “Early-Stage Neural Network Hardware Performance Analysis.” Sustainability. MDPI, 2021. https://doi.org/10.3390/su13020717.
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