| Multiple physics pretraining for physical surrogate models M McCabe, BRS Blancard, LH Parker, R Ohana, M Cranmer, A Bietti, ... arXiv preprint arXiv:2310.02994, 2023 | 11 | 2023 |
| xval: A continuous number encoding for large language models S Golkar, M Pettee, M Eickenberg, A Bietti, M Cranmer, G Krawezik, ... arXiv preprint arXiv:2310.02989, 2023 | 8 | 2023 |
| Learning to assimilate in chaotic dynamical systems M McCabe, J Brown Advances in neural information processing systems 34, 12237-12250, 2021 | 8 | 2021 |
| AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models F Lanusse, L Parker, S Golkar, M Cranmer, A Bietti, M Eickenberg, ... arXiv preprint arXiv:2310.03024, 2023 | 6 | 2023 |
| Towards Stability of Autoregressive Neural Operators M McCabe, P Harrington, S Subramanian, J Brown Transactions on Machine Learning Research 2023, 2023 | 2 | 2023 |
| Mapper comparison with wasserstein metrics M McCabe arXiv preprint arXiv:1812.06232, 2018 | 1 | 2018 |
| A Deep Learning Approach for Detection, Semantic Segmentation and Density Classification of Smoke in Satellite Imagery R Koki, J Stewart, C Kumler, M McCabe AGU Fall Meeting Abstracts 2022, H22P-1023, 2022 | | 2022 |
| Improving Deep Learning Seismic Arrival Pickers using Wavelet Transforms R Koki, A Sheehan, E Bradley, M McCabe, J Brown AGU Fall Meeting Abstracts 2022, S42C-0162, 2022 | | 2022 |
| Deep Learning Seismic Arrival Picks R Koki, A Sheehan, L Bradley, M McCabe, T Priyam | | |
| Using Differentiable Physics for Self-Supervised Assimilation of Chaotic Dynamical Systems M McCabe, J Brown | | |
Jed BrownUniversity of Colorado BoulderZweryfikowany adres z colorado.edu
