Please note that ISTA Research Explorer no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
7478 Publications
2024 | Published | Journal Article | IST-REx-ID: 18970 | 
T. Hausel, D. Maulik, A. Mellit, O. Schiffmann, and J. Shen, “Arbeitsgemeinschaft: Geometry and representation theory around the P=W conjecture,” Oberwolfach Reports, vol. 21, no. 2. EMS Press, pp. 949–1004, 2024.
[Published Version]
View
| DOI
| Download Published Version (ext.)
2024 | Published | Conference Paper | IST-REx-ID: 18975 |
I.-V. Modoranu, A. Kalinov, E. Kurtic, E. Frantar, and D.-A. Alistarh, “Error feedback can accurately compress preconditioners,” in 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 35910–35933.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18971 |
R. Arefin et al., “Unsupervised concept discovery mitigates spurious correlations,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 1672–1688.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18974 |
J. Svoboda, S. Bansal, and K. Chatterjee, “Reinforcement learning from reachability specifications: PAC guarantees with expected conditional distance,” in 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 47331–47344.
[Preprint]
View
| Download Preprint (ext.)
2024 | Published | Conference Paper | IST-REx-ID: 18977 |
T. Dettmers et al., “SpQR: A sparse-quantized representation for near-lossless LLM weight compression,” in 12th International Conference on Learning Representations, Vienna, Austria, 2024.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18998 |
O. Draganov and S. Skiena, “The shape of word embeddings: Quantifying non-isometry with topological data analysis,” in Findings of the Association for Computational Linguistics: EMNLP 2024, Miami, FL, United States, 2024, pp. 12080–12099.
[Published Version]
View
| Files available
| DOI
| arXiv
2024 | Submitted | Preprint | IST-REx-ID: 18999 |
S. Cultrera di Montesano, O. Draganov, H. Edelsbrunner, and M. Saghafian, “Chromatic topological data analysis,” arXiv. .
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 14946 |
D. Yao et al., “Multi-view causal representation learning with partial observability,” in 12th International Conference on Learning Representations, Vienna, Austria, 2024.
[Published Version]
View
| Files available
| arXiv
2024 | Published | Preprint | IST-REx-ID: 19063 |
E. Zverev, S. Abdelnabi, S. Tabesh, M. Fritz, and C. Lampert, “Can LLMs separate instructions from data? And what do we even mean by that?,” arXiv. 2024.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| arXiv
2024 | Published | Journal Article | IST-REx-ID: 17233 |
Z. LI, J. Huard, E. M. Bayer, and V. Wattelet-Boyer, “Versatile cloning strategy for efficient multigene editing in Arabidopsis,” Bio-protocol, vol. 14, no. 13. Bio-Protocol, 2024.
[Published Version]
View
| Files available
| DOI
| PubMed | Europe PMC
2024 | Published | Journal Article | IST-REx-ID: 19408 |
E. Verwimp et al., “Continual learning: Applications and the road forward,” Transactions on Machine Learning Research, vol. 2024. Transactions on Machine Learning Research, 2024.
[Published Version]
View
| Files available
| arXiv
2024 | Published | Thesis | IST-REx-ID: 17225 |
V. Li, “Towards a quantum entanglement enhanced atom interferomter,” Institute of Science and Technology Austria, 2024.
[Published Version]
View
| Files available
| DOI
2024 | Published | Thesis | IST-REx-ID: 18443 |
M. A. Sisak, “T-dual branes on hyperkähler manifolds,” Institute of Science and Technology Austria, 2024.
[Published Version]
View
| Files available
| DOI
2024 | Published | Journal Article | IST-REx-ID: 14400 |
R. Majumdar, K. Mallik, A. K. Schmuck, and S. Soudjani, “Symbolic control for stochastic systems via finite parity games,” Nonlinear Analysis: Hybrid Systems, vol. 51, no. 2. Elsevier, 2024.
[Published Version]
View
| Files available
| DOI
| WoS
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18955 |
A. Casares, M. Pilipczuk, M. Pilipczuk, U. S. Souza, and K. S. Thejaswini, “Simple and tight complexity lower bounds for solving Rabin games,” in 2024 Symposium on Simplicity in Algorithms, Alexandria, VA, United States, 2024, pp. 160–167.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2024 | Published | Journal Article | IST-REx-ID: 15252 |
L. Dello Schiavo, “A characterization of maps of bounded compression,” Mathematical Communications, vol. 29, no. 1. Udruga Matematicara Osijek, pp. 137–142, 2024.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Thesis | IST-REx-ID: 17485 |
E. Frantar, “Compressing large neural networks : Algorithms, systems and scaling laws,” Institute of Science and Technology Austria, 2024.
[Published Version]
View
| Files available
| DOI
2024 | Published | Conference Paper | IST-REx-ID: 18061 |
E. Frantar and D.-A. Alistarh, “QMoE: Sub-1-bit compression of trillion parameter models,” in Proceedings of Machine Learning and Systems, Santa Clara, CA, USA, 2024, vol. 6.
[Published Version]
View
| Files available
| Download Published Version (ext.)
2024 | Published | Conference Paper | IST-REx-ID: 18062 |
E. Frantar, C. R. Ruiz, N. Houlsby, D.-A. Alistarh, and U. Evci, “Scaling laws for sparsely-connected foundation models,” in The Twelfth International Conference on Learning Representations, Vienna, Austria, 2024.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2024 | Published | Journal Article | IST-REx-ID: 13974 |
R. Fulek, B. Gärtner, A. Kupavskii, P. Valtr, and U. Wagner, “The crossing Tverberg theorem,” Discrete and Computational Geometry, vol. 72. Springer Nature, pp. 831–848, 2024.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv