| Loss surface simplexes for mode connecting volumes and fast ensembling G Benton, W Maddox, S Lotfi, AGG Wilson International Conference on Machine Learning (ICML), 769-779, 2021 | 81 | 2021 |
| Bayesian model selection, the marginal likelihood, and generalization S Lotfi, P Izmailov, G Benton, M Goldblum, AG Wilson International Conference on Machine Learning (ICML), 14223-14247, 2022 | 78 | 2022 |
| PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization S Lotfi, M Finzi, S Kapoor, A Potapczynski, M Goldblum, AG Wilson Advances in Neural Information Processing Systems (NeurIPS) 35, 31459-31473, 2022 | 54 | 2022 |
| Dangers of bayesian model averaging under covariate shift P Izmailov, P Nicholson, S Lotfi, AG Wilson Advances in Neural Information Processing Systems (NeurIPS) 34, 3309-3322, 2021 | 50 | 2021 |
| Non-vacuous generalization bounds for large language models S Lotfi, M Finzi, Y Kuang, TGJ Rudner, M Goldblum, AG Wilson International Conference on Machine Learning (ICML), 2024 | 17 | 2024 |
| Evaluating approximate inference in Bayesian deep learning AG Wilson, S Lotfi, S Vikram, MD Hoffman, Y Gal, Y Li, MF Pradier, ... NeurIPS 2021 Competitions and Demonstrations Track, 113-124, 2022 | 17 | 2022 |
| Stochastic damped L-BFGS with controlled norm of the Hessian approximation S Lotfi, TB de Ruisselet, D Orban, A Lodi SIAM Conference on Optimization, 2020 | 7 | 2020 |
| Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models S Lotfi, Y Kuang, MA Finzi, B Amos, M Goldblum, AG Wilson Advances in Neural Information Processing Systems (NeurIPS), 2024 | 5 | 2024 |
| Evaluating Approximate Inference in Bayesian Deep Learning. 2021 AG Wilson, P Izmailov, MD Hoffman, Y Gal, Y Li, MF Pradier, S Vikram, ... URL: https://izmailovpavel. github. io/neurips_bdl_competition/files …, 2021 | 2* | 2021 |
| Stochastic First and Second Order Optimization Methods for Machine Learning S Lotfi Ecole Polytechnique, Montreal (Canada), 2020 | 2 | 2020 |
| Adaptive first-and second-order algorithms for large-scale machine learning S Lotfi, TB de Ruisselet, D Orban, A Lodi Annual Conference on Machine Learning, Optimization, and Data Science (LOD), 2021 | 1 | 2021 |
| Planning in home health care structures using reinforcement learning S Lotfi, A Khalifa, A Bellahsen, L Benabbou ICLR AI for social good workshop, 2019 | 1 | 2019 |
| Bayesian model selection, the marginal likelihood, and generalization S Lotfi, P Izmailov, G Benton, M Goldblum, AG Wilson Journal of Machine Learning Research (JMLR), 2023 | | 2023 |
| Ocular Cataract Identification Using Deep Convolutional Neural Networks FME Manuel, SM Saide, FDMA Ali, S Lotfi International Conference on Artificial Intelligence, Big Data, Computing and …, 2023 | | 2023 |
| Stochastic adaptive regularization with dynamic sampling for machine learning S Lotfi, D Orban, A Lodi Les Cahiers du GERAD ISSN 711, 2440, 2020 | | 2020 |
Andrew Gordon WilsonNew York UniversityE-mail megerősítve itt: cims.nyu.edu