Please note that LibreCat no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
5181 Publications
2021 |Published| Journal Article | IST-REx-ID: 10191 |
Bui, Truc Lam, et al. “The Reads-from Equivalence for the TSO and PSO Memory Models.” Proceedings of the ACM on Programming Languages, vol. 5, no. OOPSLA, 164, Association for Computing Machinery, 2021, doi:10.1145/3485541.
[Published Version]
View
| Files available
| DOI
| arXiv
2021 |Submitted| Preprint | IST-REx-ID: 10013 |
Hensel, Sebastian, and Tim Laux. “Weak-Strong Uniqueness for the Mean Curvature Flow of Double Bubbles.” ArXiv, 2108.01733, doi:10.48550/arXiv.2108.01733.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| arXiv
2021 |Published| Thesis | IST-REx-ID: 10030 |
Portinale, Lorenzo. Discrete-to-Continuum Limits of Transport Problems and Gradient Flows in the Space of Measures. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10030.
[Published Version]
View
| Files available
| DOI
2021 |Published| Thesis | IST-REx-ID: 9920 |
Peruzzo, Matilda. Geometric Superinductors and Their Applications in Circuit Quantum Electrodynamics. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:9920.
[Published Version]
View
| Files available
| DOI
2021 |Published| Conference Paper | IST-REx-ID: 10432 |
Nadiradze, Giorgi, et al. “Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent.” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 10, 2021, pp. 9037–45.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2021 |Published| Conference Paper | IST-REx-ID: 10041 |
Kamath Hosdurg, Chethan, et al. “Limits on the Adaptive Security of Yao’s Garbling.” 41st Annual International Cryptology Conference, Part II , vol. 12826, Springer Nature, 2021, pp. 486–515, doi:10.1007/978-3-030-84245-1_17.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
2021 |Published| Conference Paper | IST-REx-ID: 10049 |
Klein, Karen, et al. “Keep the Dirt: Tainted TreeKEM, Adaptively and Actively Secure Continuous Group Key Agreement.” 2021 IEEE Symposium on Security and Privacy , IEEE, 2021, pp. 268–84, doi:10.1109/sp40001.2021.00035.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
2021 |Published| Conference Paper | IST-REx-ID: 10044 |
Kamath Hosdurg, Chethan, et al. “On Treewidth, Separators and Yao’s Garbling.” 19th Theory of Cryptography Conference 2021, 2021/926, International Association for Cryptologic Research, 2021.
[Preprint]
View
| Files available
| Download Preprint (ext.)
2021 |Published| Thesis | IST-REx-ID: 10422 |
Piankov, Anton. Towards Designer Materials Using Customizable Particle Shape. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10422.
[Published Version]
View
| Files available
| DOI
2021 |Submitted| Preprint | IST-REx-ID: 10803 |
Konstantinov, Nikola H., and Christoph Lampert. “Fairness through Regularization for Learning to Rank.” ArXiv, 2102.05996, doi:10.48550/arXiv.2102.05996.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| arXiv
2021 |Submitted| Preprint | IST-REx-ID: 10762 |
Rzadkowski, Wojciech, et al. “Artificial Neural Network States for Non-Additive Systems.” ArXiv, doi:10.48550/arXiv.2105.15193.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| arXiv
2021 |Published| Thesis | IST-REx-ID: 9418 |
Phuong, Mary. Underspecification in Deep Learning. Institute of Science and Technology Austria, 2021, doi:10.15479/AT:ISTA:9418.
[Published Version]
View
| Files available
| DOI
2021 |Published| Conference Paper | IST-REx-ID: 14177 |
Träuble, Frederik, et al. “On Disentangled Representations Learned from Correlated Data.” Proceedings of the 38th International Conference on Machine Learning, vol. 139, ML Research Press, 2021, pp. 10401–12.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
2021 |Published| Conference Paper | IST-REx-ID: 14176 |
Yèche, Hugo, et al. “Neighborhood Contrastive Learning Applied to Online Patient Monitoring.” Proceedings of 38th International Conference on Machine Learning, vol. 139, ML Research Press, 2021, pp. 11964–74.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2021 |Published| Conference Paper | IST-REx-ID: 14182 |
Träuble, Frederik, et al. “Backward-Compatible Prediction Updates: A Probabilistic Approach.” 35th Conference on Neural Information Processing Systems, vol. 34, 2021, pp. 116–28.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2021 |Published| Conference Paper | IST-REx-ID: 14181 |
Dresdner, Gideon, et al. “Boosting Variational Inference with Locally Adaptive Step-Sizes.” Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, 2021, pp. 2337–43, doi:10.24963/ijcai.2021/322.
[Published Version]
View
| DOI
| Download Published Version (ext.)
| arXiv
2021 |Published| Conference Paper | IST-REx-ID: 14179 |
Kügelgen, Julius von, et al. “Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style.” Advances in Neural Information Processing Systems, vol. 34, 2021, pp. 16451–67.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2021 |Published| Conference Paper | IST-REx-ID: 14180 |
Rahaman, Nasim, et al. “Dynamic Inference with Neural Interpreters.” Advances in Neural Information Processing Systems, vol. 34, 2021, pp. 10985–98.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2021 |Published| Journal Article | IST-REx-ID: 14117 |
Scholkopf, Bernhard, et al. “Toward Causal Representation Learning.” Proceedings of the IEEE, vol. 109, no. 5, Institute of Electrical and Electronics Engineers, 2021, pp. 612–34, doi:10.1109/jproc.2021.3058954.
[Published Version]
View
| DOI
| Download Published Version (ext.)
| arXiv
2021 |Published| Conference Paper | IST-REx-ID: 14178 |
Dittadi, Andrea, et al. “On the Transfer of Disentangled Representations in Realistic Settings.” The Ninth International Conference on Learning Representations, 2021.
[Preprint]
View
| Download Preprint (ext.)
| arXiv