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6767 Publications

2024 | Published | Journal Article | IST-REx-ID: 15097 | OA
Schmidt H, Rast S, Bao J, et al. Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model. Geoscientific Model Development. 2024;17(4):1563-1584. doi:10.5194/gmd-17-1563-2024
[Published Version] View | Files available | DOI | WoS
 
2024 | Published | Journal Article | IST-REx-ID: 15186 | OA
Hwong Y-L, Muller CJ. The unreasonable efficiency of total rain evaporation removal in triggering convective self‐aggregation. Geophysical Research Letters. 2024;51(6). doi:10.1029/2023gl106523
[Published Version] View | Files available | DOI | WoS
 
2024 | Published | Journal Article | IST-REx-ID: 15165 | OA
GOSWAMI BB. A pre-monsoon signal of false alarms of Indian monsoon droughts. Geophysical Research Letters. 2024;51(5). doi:10.1029/2023GL106569
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2024 | Published | Journal Article | IST-REx-ID: 18708 | OA
Paik S, Kim D, An SI, et al. Exploring causes of distinct regional and subseasonal Indian summer monsoon precipitation responses to CO2 removal. npj Climate and Atmospheric Science. 2024;7. doi:10.1038/s41612-024-00858-0
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2024 | Research Data Reference | IST-REx-ID: 19307 | OA
Hwong Y-L, Muller CJ. Data - The unreasonable efficiency of total rain evaporation removal in triggering convective self-aggregation. 2024. doi:10.5281/ZENODO.10687169
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2024 | Published | Journal Article | IST-REx-ID: 17203 | OA
Hafner C, Ly M, Wojtan C. Spin-it faster: Quadrics solve all topology optimization problems that depend only on mass moments. Transactions on Graphics. 2024;43(4). doi:10.1145/3658194
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2024 | Published | Journal Article | IST-REx-ID: 15313 | OA
Agasthya LN, Muller CJ. Dynamics and scaling of internally cooled convection. Communications in Nonlinear Science and Numerical Simulation. 2024;134. doi:10.1016/j.cnsns.2024.108011
[Published Version] View | Files available | DOI | WoS | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 17411 | OA
Scott JA, Zakerinia H, Lampert C. 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 JA, Cahill Á. Improved modelling of federated datasets using mixtures-of-Dirichlet-multinomials. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:44012-44037.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18118 | OA
Zakerinia H, Behjati A, Lampert C. More flexible PAC-Bayesian meta-learning by learning learning algorithms. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:58122-58139.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 17332 | OA
Kokorin I, Yudov V, Aksenov V, Alistarh D-A. Wait-free trees with asymptotically-efficient range queries. In: 2024 IEEE International Parallel and Distributed Processing Symposium. IEEE; 2024:169-179. doi:10.1109/IPDPS57955.2024.00023
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 15011 | OA
Kurtic E, Hoefler T, Alistarh D-A. How to prune your language model: Recovering accuracy on the “Sparsity May Cry” benchmark. In: Proceedings of Machine Learning Research. Vol 234. ML Research Press; 2024:542-553.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18070
Chatterjee B, Kungurtsev V, Alistarh D-A. Federated SGD with local asynchrony. In: Proceedings of the 44th International Conference on Distributed Computing Systems. IEEE; 2024:857-868. doi:10.1109/ICDCS60910.2024.00084
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2024 | Published | Conference Paper | IST-REx-ID: 17329 | OA
Alistarh D-A, Chatterjee K, Karrabi M, Lazarsfeld JM. Game dynamics and equilibrium computation in the population protocol model. In: Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed Computing. Association for Computing Machinery; 2024:40-49. doi:10.1145/3662158.3662768
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2024 | Published | Conference Paper | IST-REx-ID: 18121 | OA
Moakhar AS, Iofinova EB, Frantar E, Alistarh D-A. SPADE: Sparsity-guided debugging for deep neural networks. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:45955-45987.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18976 | OA
Islamov R, Safaryan M, Alistarh D-A. AsGrad: A sharp unified analysis of asynchronous-SGD algorithms. In: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics. Vol 238. ML Research Press; 2024:649-657.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18113 | OA
Egiazarian V, Panferov A, Kuznedelev D, Frantar E, Babenko A, Alistarh D-A. Extreme compression of large language models via additive quantization. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:12284-12303.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18975 | OA
Modoranu I-V, Kalinov A, Kurtic E, Frantar E, Alistarh D-A. Error feedback can accurately compress preconditioners. In: 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:35910-35933.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18977 | OA
Dettmers T, Svirschevski RA, Egiazarian V, et al. 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 H, Talaei S, Nadiradze G, Alistarh D-A. Communication-efficient federated learning with data and client heterogeneity. In: Proceedings of the 27th International Conference on Artificial Intelligence and Statistics. Vol 238. ML Research Press; 2024:3448-3456.
[Preprint] View | Download Preprint (ext.) | arXiv
 

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