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@@ -116,14 +116,26 @@ <h3>Journals</h3>
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<h3>Conference</h3>
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<ul>
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<li><p>Tao Yu, <i>Gaurav Gupta</i>, Karthick Gopalswamy, Amith Mamidala, Hao Zhou, Jeffrey Huynh, Youngsuk Park, Ron Diamant, Anoop Deoras, and Luke Huan <br/>
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<b>Collage: Light-Weight Low-Precision Strategy for LLM Training</b><ahref="https://arxiv.org/abs/2405.03637">[arXiv</a>]<br/>
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in ICML: 41th International Conference on Machine Learning, July 2024.</p>
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</li>
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</ul>
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<ul>
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<li><p>S. Chandra Mouli, Danielle C. Maddix, Shima Alizadeh, <i>Gaurav Gupta</i>, Andrew Stuart, Michael W. Mahoney, and Yuyang Wang <br/>
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<b>Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs</b><ahref="https://arxiv.org/abs/2403.10642">[arXiv</a>]<br/>
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in ICML: 41th International Conference on Machine Learning, July 2024.</p>
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</li>
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</ul>
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<ul>
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<li><p>Derek Hansen, Danielle C. Maddix, Shima Alizadeh, <i>Gaurav Gupta</i>, Michael W. Mahoney <br/>
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<b>Learning Physical Models that Can Respect Conservation Laws</b><ahref="https://arxiv.org/abs/2302.11002">[arXiv</a>]<br/>
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in ICML: 40th International Conference on Machine Learning, July 2023.</p>
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</li>
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<li><p>Hilaf Hasson, Danielle C. Maddix, Bernie Wang, <i>Gaurav Gupta</i>, Youngsuk Park <br/>
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<b>Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting</b><br/>
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<b>Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting</b><ahref="https://arxiv.org/abs/2305.15786">[arXiv</a>]<br/>
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in ICML: 40th International Conference on Machine Learning, July 2023.</p>
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</li>
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Page generated 2023-05-01 23:25:40 PDT, by <ahref="http://jemdoc.jaboc.net/">jemdoc</a>.
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Page generated 2024-05-07 11:28:41 PDT, by <ahref="http://jemdoc.jaboc.net/">jemdoc</a>.
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