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12340 Publications


2024 | Published | Journal Article | IST-REx-ID: 15165 | OA
GOSWAMI, BIDYUT B. “A Pre-Monsoon Signal of False Alarms of Indian Monsoon Droughts.” Geophysical Research Letters. Wiley, 2024. https://doi.org/10.1029/2023GL106569.
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2024 | Published | Journal Article | IST-REx-ID: 18708 | OA
Paik, Seungmok, Daehyun Kim, Soon Il An, Hyoeun Oh, Jongsoo Shin, BIDYUT B GOSWAMI, Seung Ki Min, and Sanjit Kumar Mondal. “Exploring Causes of Distinct Regional and Subseasonal Indian Summer Monsoon Precipitation Responses to CO2 Removal.” Npj Climate and Atmospheric Science. Springer Nature, 2024. https://doi.org/10.1038/s41612-024-00858-0.
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2024 | Research Data Reference | IST-REx-ID: 19307 | OA
Hwong, Yi-Ling, and Caroline J Muller. “Data - The Unreasonable Efficiency of Total Rain Evaporation Removal in Triggering Convective Self-Aggregation.” Zenodo, 2024. https://doi.org/10.5281/ZENODO.10687169.
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2024 | Published | Journal Article | IST-REx-ID: 17203 | OA
Hafner, Christian, Mickaël Ly, and Chris Wojtan. “Spin-It Faster: Quadrics Solve All Topology Optimization Problems That Depend Only on Mass Moments.” Transactions on Graphics. Association for Computing Machinery, 2024. https://doi.org/10.1145/3658194.
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2024 | Published | Journal Article | IST-REx-ID: 15313 | OA
Agasthya, Lokahith N, and Caroline J Muller. “Dynamics and Scaling of Internally Cooled Convection.” Communications in Nonlinear Science and Numerical Simulation. Elsevier, 2024. https://doi.org/10.1016/j.cnsns.2024.108011.
[Published Version] View | Files available | DOI | WoS | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 17411 | OA
Scott, Jonathan A, Hossein Zakerinia, and Christoph Lampert. “PEFLL: Personalized Federated Learning by Learning to Learn.” In 12th International Conference on Learning Representations. OpenReview, 2024.
[Published Version] View | Files available | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18120 | OA
Scott, Jonathan A, and Áine Cahill. “Improved Modelling of Federated Datasets Using Mixtures-of-Dirichlet-Multinomials.” In Proceedings of the 41st International Conference on Machine Learning, 235:44012–37. ML Research Press, 2024.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18118 | OA
Zakerinia, Hossein, Amin Behjati, and Christoph Lampert. “More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms.” In Proceedings of the 41st International Conference on Machine Learning, 235:58122–39. ML Research Press, 2024.
[Published Version] View | Download Published Version (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 17332 | OA
Kokorin, Ilya, Victor Yudov, Vitaly Aksenov, and Dan-Adrian Alistarh. “Wait-Free Trees with Asymptotically-Efficient Range Queries.” In 2024 IEEE International Parallel and Distributed Processing Symposium, 169–79. IEEE, 2024. https://doi.org/10.1109/IPDPS57955.2024.00023.
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2024 | Published | Conference Paper | IST-REx-ID: 15011 | OA
Kurtic, Eldar, Torsten Hoefler, and Dan-Adrian Alistarh. “How to Prune Your Language Model: Recovering Accuracy on the ‘Sparsity May Cry’ Benchmark.” In Proceedings of Machine Learning Research, 234:542–53. ML Research Press, 2024.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18070
Chatterjee, Bapi, Vyacheslav Kungurtsev, and Dan-Adrian Alistarh. “Federated SGD with Local Asynchrony.” In Proceedings of the 44th International Conference on Distributed Computing Systems, 857–68. IEEE, 2024. https://doi.org/10.1109/ICDCS60910.2024.00084.
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2024 | Published | Conference Paper | IST-REx-ID: 17329 | OA
Alistarh, Dan-Adrian, Krishnendu Chatterjee, Mehrdad Karrabi, and John M Lazarsfeld. “Game Dynamics and Equilibrium Computation in the Population Protocol Model.” In Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed Computing, 40–49. Association for Computing Machinery, 2024. https://doi.org/10.1145/3662158.3662768.
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2024 | Published | Conference Paper | IST-REx-ID: 18121 | OA
Moakhar, Arshia Soltani, Eugenia B Iofinova, Elias Frantar, and Dan-Adrian Alistarh. “SPADE: Sparsity-Guided Debugging for Deep Neural Networks.” In Proceedings of the 41st International Conference on Machine Learning, 235:45955–87. ML Research Press, 2024.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18976 | OA
Islamov, Rustem, Mher Safaryan, and Dan-Adrian Alistarh. “AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms.” In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, 238:649–57. ML Research Press, 2024.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18113 | OA
Egiazarian, Vage, Andrei Panferov, Denis Kuznedelev, Elias Frantar, Artem Babenko, and Dan-Adrian Alistarh. “Extreme Compression of Large Language Models via Additive Quantization.” In Proceedings of the 41st International Conference on Machine Learning, 235:12284–303. ML Research Press, 2024.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18975 | OA
Modoranu, Ionut-Vlad, Aleksei Kalinov, Eldar Kurtic, Elias Frantar, and Dan-Adrian Alistarh. “Error Feedback Can Accurately Compress Preconditioners.” In 41st International Conference on Machine Learning, 235:35910–33. ML Research Press, 2024.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18977 | OA
Dettmers, Tim, Ruslan A. Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, and Dan-Adrian Alistarh. “SpQR: A Sparse-Quantized Representation for near-Lossless LLM Weight Compression.” In 12th International Conference on Learning Representations. OpenReview, 2024.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 17093 | OA
Zakerinia, Hossein, Shayan Talaei, Giorgi Nadiradze, and Dan-Adrian Alistarh. “Communication-Efficient Federated Learning with Data and Client Heterogeneity.” In Proceedings of the 27th International Conference on Artificial Intelligence and Statistics, 238:3448–56. ML Research Press, 2024.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18117 | OA
Nikdan, Mahdi, Soroush Tabesh, Elvir Crncevic, and Dan-Adrian Alistarh. “RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation.” In Proceedings of the 41st International Conference on Machine Learning, 235:38187–206. ML Research Press, 2024.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2024 | Published | Journal Article | IST-REx-ID: 15315 | OA
Brückner, David, and Chase P. Broedersz. “Learning Dynamical Models of Single and Collective Cell Migration: A Review.” Reports on Progress in Physics. IOP Publishing, 2024. https://doi.org/10.1088/1361-6633/ad36d2.
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