| Large language models are zero-shot time series forecasters N Gruver, M Finzi, S Qiu, AG Wilson Advances in Neural Information Processing Systems 36, 2024 | 334 | 2024 |
| Simple and fast group robustness by automatic feature reweighting S Qiu, A Potapczynski, P Izmailov, AG Wilson International Conference on Machine Learning, 28448-28467, 2023 | 49 | 2023 |
| Holistic approach to predicting top quark kinematic properties with the covariant particle transformer S Qiu, S Han, X Ju, B Nachman, H Wang Physical Review D 107 (11), 114029, 2023 | 24 | 2023 |
| Function-space regularization in neural networks: A probabilistic perspective TGJ Rudner, S Kapoor, S Qiu, AG Wilson International Conference on Machine Learning, 29275-29290, 2023 | 14 | 2023 |
| Model-independent search for the presence of new physics in events including H → γγ with = 13 TeV pp data recorded by the ATLAS detector at the LHC G Aad, B Abbott, K Abeling, SH Abidi, A Aboulhorma, H Abramowicz, ... Journal of High Energy Physics 2023 (7), 1-51, 2023 | 9 | 2023 |
| Compute Better Spent: Replacing Dense Layers with Structured Matrices S Qiu, A Potapczynski, M Finzi, M Goldblum, AG Wilson arXiv preprint arXiv:2406.06248, 2024 | 7 | 2024 |
| Should we learn most likely functions or parameters? S Qiu, TGJ Rudner, S Kapoor, AG Wilson Advances in Neural Information Processing Systems 36, 2024 | 7 | 2024 |
| Parton labeling without matching: unveiling emergent labelling capabilities in regression models S Qiu, S Han, X Ju, B Nachman, H Wang The European Physical Journal C 83 (7), 622, 2023 | 5 | 2023 |
| Model-independent search for the presence of new physics in events including with = 13 TeV pp data recorded by the ATLAS detector at the LHC ATLAS collaboration arXiv preprint arXiv:2301.10486, 2023 | 5 | 2023 |
| Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices A Potapczynski, S Qiu, M Finzi, C Ferri, Z Chen, M Goldblum, B Bruss, ... arXiv preprint arXiv:2410.02117, 2024 | | 2024 |
| Transferring Knowledge from Large Foundation Models to Small Downstream Models S Qiu, B Han, DC Maddix, S Zhang, Y Wang, AG Wilson arXiv preprint arXiv:2406.07337, 2024 | | 2024 |
| Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks S Qiu, A Agarwala, J Pennington, L Xiao OPT 2024: Optimization for Machine Learning, 0 | | |
Andrew Gordon WilsonNew York UniversityE-mailová adresa ověřena na: cims.nyu.edu