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6768 Publications

2024 | Published | Journal Article | IST-REx-ID: 18940 | OA
Knabl, P., Schauer, A., Pomreinke, A. P., Zimmermann, B., Rogers, K. W., Čapek, D., … Genikhovich, G. (2024). Analysis of SMAD1/5 target genes in a sea anemone reveals ZSWIM4-6 as a novel BMP signaling modulator. ELife. eLife Sciences Publications. https://doi.org/10.7554/elife.80803
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2024 | Published | Journal Article | IST-REx-ID: 15097 | OA
Schmidt, H., Rast, S., Bao, J., Cassim, A., Fang, S. W., Jimenez-De La Cuesta, D., … Stevens, B. (2024). Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model. Geoscientific Model Development. European Geosciences Union. https://doi.org/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, C. J. (2024). The unreasonable efficiency of total rain evaporation removal in triggering convective self‐aggregation. Geophysical Research Letters. Wiley. https://doi.org/10.1029/2023gl106523
[Published Version] View | Files available | DOI | WoS
 
2024 | Published | Journal Article | IST-REx-ID: 15165 | OA
GOSWAMI, B. B. (2024). A pre-monsoon signal of false alarms of Indian monsoon droughts. Geophysical Research Letters. Wiley. https://doi.org/10.1029/2023GL106569
[Published Version] View | Files available | DOI | WoS
 
2024 | Published | Journal Article | IST-REx-ID: 18708 | OA
Paik, S., Kim, D., An, S. I., Oh, H., Shin, J., GOSWAMI, B. B., … Mondal, S. K. (2024). Exploring causes of distinct regional and subseasonal Indian summer monsoon precipitation responses to CO2 removal. Npj Climate and Atmospheric Science. Springer Nature. https://doi.org/10.1038/s41612-024-00858-0
[Published Version] View | Files available | DOI | WoS
 
2024 | Research Data Reference | IST-REx-ID: 19307 | OA
Hwong, Y.-L., & Muller, C. J. (2024). Data - The unreasonable efficiency of total rain evaporation removal in triggering convective self-aggregation. Zenodo. https://doi.org/10.5281/ZENODO.10687169
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2024 | Published | Journal Article | IST-REx-ID: 17203 | OA
Hafner, C., Ly, M., & Wojtan, C. (2024). Spin-it faster: Quadrics solve all topology optimization problems that depend only on mass moments. Transactions on Graphics. Denver, Colorado: Association for Computing Machinery. https://doi.org/10.1145/3658194
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2024 | Published | Journal Article | IST-REx-ID: 15313 | OA
Agasthya, L. N., & Muller, C. J. (2024). Dynamics and scaling of internally cooled convection. Communications in Nonlinear Science and Numerical Simulation. Elsevier. 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, J. A., Zakerinia, H., & Lampert, C. (2024). PEFLL: Personalized federated learning by learning to learn. In 12th International Conference on Learning Representations. Vienna, Austria: OpenReview.
[Published Version] View | Files available | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18120 | OA
Scott, J. A., & Cahill, Á. (2024). Improved modelling of federated datasets using mixtures-of-Dirichlet-multinomials. In Proceedings of the 41st International Conference on Machine Learning (Vol. 235, pp. 44012–44037). Vienna, Austria: ML Research Press.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18118 | OA
Zakerinia, H., Behjati, A., & Lampert, C. (2024). More flexible PAC-Bayesian meta-learning by learning learning algorithms. In Proceedings of the 41st International Conference on Machine Learning (Vol. 235, pp. 58122–58139). Vienna, Austria: ML Research Press.
[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. (2024). Wait-free trees with asymptotically-efficient range queries. In 2024 IEEE International Parallel and Distributed Processing Symposium (pp. 169–179). San Francisco, CA, United States: IEEE. https://doi.org/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. (2024). How to prune your language model: Recovering accuracy on the “Sparsity May Cry” benchmark. In Proceedings of Machine Learning Research (Vol. 234, pp. 542–553). Hongkong, China: ML Research Press.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18070
Chatterjee, B., Kungurtsev, V., & Alistarh, D.-A. (2024). Federated SGD with local asynchrony. In Proceedings of the 44th International Conference on Distributed Computing Systems (pp. 857–868). Jersey City, NJ, United States: IEEE. https://doi.org/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, J. M. (2024). Game dynamics and equilibrium computation in the population protocol model. In Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed Computing (pp. 40–49). Nantes, France: Association for Computing Machinery. https://doi.org/10.1145/3662158.3662768
[Published Version] View | Files available | DOI
 
2024 | Published | Conference Paper | IST-REx-ID: 18121 | OA
Moakhar, A. S., Iofinova, E. B., Frantar, E., & Alistarh, D.-A. (2024). SPADE: Sparsity-guided debugging for deep neural networks. In Proceedings of the 41st International Conference on Machine Learning (Vol. 235, pp. 45955–45987). Vienna, Austria: ML Research Press.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18976 | OA
Islamov, R., Safaryan, M., & Alistarh, D.-A. (2024). AsGrad: A sharp unified analysis of asynchronous-SGD algorithms. In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (Vol. 238, pp. 649–657). Valencia, Spain: ML Research Press.
[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. (2024). Extreme compression of large language models via additive quantization. In Proceedings of the 41st International Conference on Machine Learning (Vol. 235, pp. 12284–12303). Vienna, Austria: ML Research Press.
[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. (2024). Error feedback can accurately compress preconditioners. In 41st International Conference on Machine Learning (Vol. 235, pp. 35910–35933). Vienna, Austria: ML Research Press.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18977 | OA
Dettmers, T., Svirschevski, R. A., Egiazarian, V., Kuznedelev, D., Frantar, E., Ashkboos, S., … Alistarh, D.-A. (2024). SpQR: A sparse-quantized representation for near-lossless LLM weight compression. In 12th International Conference on Learning Representations. Vienna, Austria: OpenReview.
[Preprint] View | Download Preprint (ext.) | arXiv
 

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