| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 4802 | 2021 |
| Hungry Hungry Hippos: Towards Language Modeling with State Space Models DY Fu, T Dao, KK Saab, AW Thomas, A Rudra, C Re International Conference on Learning Representations (ICLR 2023), 2023 | 467 | 2023 |
| HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution E Nguyen, M Poli, M Faizi, A Thomas, C Birch-Sykes, M Wornow, A Patel, ... Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 2023 | 267 | 2023 |
| Sequence modeling and design from molecular to genome scale with Evo E Nguyen, M Poli, MG Durrant, B Kang, D Katrekar, DB Li, LJ Bartie, ... Science 386 (6723), eado9336, 2024 | 128 | 2024 |
| Analyzing Neuroimaging Data Through Recurrent Deep Learning Models AW Thomas, HR Heekeren, KR Müller, W Samek Frontiers in Neuroscience 13, 1321, 2019 | 120* | 2019 |
| Gaze bias differences capture individual choice behaviour AW Thomas, F Molter, I Krajbich, HR Heekeren, PNC Mohr Nature Human Behaviour, 1, 2019 | 99 | 2019 |
| Simple Hardware-Efficient Long Convolutions for Sequence Modeling DY Fu, EL Epstein, E Nguyen, AW Thomas, M Zhang, T Dao, A Rudra, ... International Conference on Machine Learning (ICML 2023), 2023 | 59 | 2023 |
| Self-Supervised Learning Of Brain Dynamics From Broad Neuroimaging Data AW Thomas, C Ré, RA Poldrack Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 2022 | 55 | 2022 |
| Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture DY Fu, S Arora, J Grogan, I Johnson, S Eyuboglu, AW Thomas, B Spector, ... Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 2023 | 47 | 2023 |
| Uncovering the computational mechanisms underlying many-alternative choice AW Thomas, F Molter, I Krajbich Elife 10, e57012, 2021 | 38 | 2021 |
| Deep transfer learning for whole-brain FMRI analyses AW Thomas, KR Müller, W Samek International Workshop on Machine Learning in Clinical Neuroimaging at …, 2019 | 27 | 2019 |
| Interpreting mental state decoding with deep learning models AW Thomas, C Ré, RA Poldrack Trends in Cognitive Sciences 26 (11), 972-986, 2022 | 20* | 2022 |
| Gaze-dependent evidence accumulation predicts multi-alternative risky choice behaviour F Molter, AW Thomas, SA Huettel, HR Heekeren, PNC Mohr PLOS Computational Biology 18 (7), e1010283, 2022 | 20 | 2022 |
| Mechanistic Design and Scaling of Hybrid Architectures M Poli, AW Thomas, E Nguyen, P Ponnusamy, B Deiseroth, K Kersting, ... arXiv preprint arXiv:2403.17844, 2024 | 19 | 2024 |
| Evaluating deep transfer learning for whole-brain cognitive decoding AW Thomas, U Lindenberger, W Samek, KR Müller Journal of the Franklin Institute 360 (13), 9754-9787, 2023 | 14 | 2023 |
| GLAMbox: A Python toolbox for investigating the association between gaze allocation and decision behaviour F Molter, AW Thomas, HR Heekeren, PNC Mohr PloS one 14 (12), e0226428, 2019 | 10 | 2019 |
| Benchmarking explanation methods for mental state decoding with deep learning models AW Thomas, C Ré, RA Poldrack NeuroImage, 120109, 2023 | 8* | 2023 |
| Differentiable programming for functional connectomics R Ciric, AW Thomas, O Esteban, RA Poldrack 2nd Machine Learning for Health Symposium at NeurIPS 2022, 2022 | 2 | 2022 |
| STAR: Synthesis of Tailored Architectures AW Thomas, R Parnichkun, A Amini, S Massaroli, M Poli arXiv preprint arXiv:2411.17800, 2024 | | 2024 |
| Deep Learning for Whole-Brain Cognitive Decoding KR Müller, AW Thomas, W Samek 2022 10th International Winter Conference on Brain-Computer Interface (BCI), 1-3, 2022 | | 2022 |
Christopher RéComputer Science, Stanford UniversityVahvistettu sähköpostiosoite verkkotunnuksessa cs.stanford.edu