| 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 | 55 | 2023 |
| Multiple Physics Pretraining for Spatiotemporal Surrogate Models M McCabe, B Régaldo-Saint Blancard, LH Parker, R Ohana, M Cranmer, ... The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | 48* | 2024 |
| Field-level simulation-based inference of galaxy clustering with convolutional neural networks P Lemos*, L Parker*, CH Hahn, S Ho, M Eickenberg, J Hou, E Massara, ... Physical Review D 109 (8), 083536, 2024 | 41* | 2024 |
| AstroCLIP: a cross-modal foundation model for galaxies L Parker, F Lanusse, S Golkar, L Sarra, M Cranmer, A Bietti, M Eickenberg, ... Monthly Notices of the Royal Astronomical Society 531 (4), 4990-5011, 2024 | 36* | 2024 |
| Cosmological constraints from the redshift-space galaxy skew spectra J Hou, AM Dizgah, CH Hahn, M Eickenberg, S Ho, P Lemos, E Massara, ... Physical Review D 109 (10), 103528, 2024 | 15* | 2024 |
| Galaxy clustering analysis with SimBIG and the wavelet scattering transform B Régaldo-Saint Blancard, CH Hahn, S Ho, J Hou, P Lemos, E Massara, ... Physical Review D 109 (8), 083535, 2024 | 14* | 2024 |
| Cosmological constraints from the nonlinear galaxy bispectrum CH Hahn, M Eickenberg, S Ho, J Hou, P Lemos, E Massara, C Modi, ... Physical Review D 109 (8), 083534, 2024 | 13 | 2024 |
| Neural collapse in the intermediate hidden layers of classification neural networks L Parker, E Onal, A Stengel, J Intrater arXiv preprint arXiv:2308.02760, 2023 | 9 | 2023 |
| The well: a large-scale collection of diverse physics simulations for machine learning R Ohana, M McCabe, L Meyer, R Morel, F Agocs, M Beneitez, M Berger, ... Advances in Neural Information Processing Systems 37, 44989-45037, 2025 | 3 | 2025 |
| Cosmological constraints from non-Gaussian and nonlinear galaxy clustering using the SimBIG inference framework CH Hahn, P Lemos, L Parker, B Régaldo-Saint Blancard, M Eickenberg, ... Nature Astronomy, 1-11, 2024 | 3 | 2024 |
| {\sc SimBIG}: Cosmological constraints using simulation-based inference of galaxy clustering with marked power spectra E Massara, CH Hahn, M Eickenberg, S Ho, J Hou, P Lemos, C Modi, ... arXiv preprint arXiv:2404.04228, 2024 | 3 | 2024 |
| Recovering Galaxy Cluster Convergence from Lensed CMB with Generative Adversarial Networks L Parker, D Han, P Lemos, S Ho arXiv preprint arXiv:2211.08990, 2022 | 2 | 2022 |
| The multimodal universe: enabling large-scale machine learning with 100 TB of astronomical scientific data E Angeloudi, J Audenaert, M Bowles, BM Boyd, D Chemaly, B Cherinka, ... Advances in Neural Information Processing Systems 37, 57841-57913, 2024 | 1 | 2024 |
| The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning R Ohana, M McCabe, L Meyer, R Morel, FJ Agocs, M Beneitez, M Berger, ... arXiv preprint arXiv:2412.00568, 2024 | | 2024 |
| Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task S Golkar, A Bietti, M Pettee, M Eickenberg, M Cranmer, K Hirashima, ... arXiv preprint arXiv:2406.02585, 2024 | | 2024 |
| Ho, S. xval: A continuous number encoding for large language models S Golkar, M Pettee, M Eickenberg, A Bietti, M Cranmer, G Krawezik, ... Neural Information Processing Systems (NeurIPS) AI for Science Workshop, 2023 | | 2023 |
Shirley HoFlatiron Institute, Center for Computational AstrophysicsVerified email at flatironinstitute.org