| TDCOSMO-IV. Hierarchical time-delay cosmography–joint inference of the Hubble constant and galaxy density profiles S Birrer, AJ Shajib, A Galan, M Millon, T Treu, A Agnello, M Auger, ... Astronomy & Astrophysics 643, A165, 2020 | 366 | 2020 |
| lenstronomy II: A gravitational lensing software ecosystem S Birrer, AJ Shajib, D Gilman, A Galan, J Aalbers, M Millon, R Morgan, ... arXiv preprint arXiv:2106.05976, 2021 | 165 | 2021 |
| Hierarchical inference with bayesian neural networks: An application to strong gravitational lensing S Wagner-Carena, JW Park, S Birrer, PJ Marshall, A Roodman, ... The Astrophysical Journal 909 (2), 187, 2021 | 62 | 2021 |
| The lsst desc dc2 simulated sky survey B Abolfathi, D Alonso, R Armstrong, É Aubourg, H Awan, YN Babuji, ... The Astrophysical Journal Supplement Series 253 (1), 31, 2021 | 50 | 2021 |
| Time delay lens modelling challenge X Ding, T Treu, S Birrer, GCF Chen, J Coles, P Denzel, M Frigo, A Galan, ... Monthly Notices of the Royal Astronomical Society 503 (1), 1096-1123, 2021 | 49 | 2021 |
| GAUCHE: a library for Gaussian processes in chemistry RR Griffiths, L Klarner, H Moss, A Ravuri, S Truong, Y Du, S Stanton, ... Advances in Neural Information Processing Systems 36, 2024 | 41 | 2024 |
| Large-scale gravitational lens modeling with Bayesian neural networks for accurate and precise inference of the Hubble constant JW Park, S Wagner-Carena, S Birrer, PJ Marshall, JYY Lin, A Roodman, ... The Astrophysical Journal 910 (1), 39, 2021 | 40 | 2021 |
| DeepZipper: a novel deep-learning architecture for lensed supernovae identification R Morgan, B Nord, K Bechtol, SJ González, E Buckley-Geer, A Möller, ... The Astrophysical Journal 927 (1), 109, 2022 | 14 | 2022 |
| Propertydag: Multi-objective bayesian optimization of partially ordered, mixed-variable properties for biological sequence design JW Park, S Stanton, S Saremi, A Watkins, H Dwyer, V Gligorijevic, ... arXiv preprint arXiv:2210.04096, 2022 | 13 | 2022 |
| Latent stochastic differential equations for modeling quasar variability and inferring black hole properties J Fagin, JW Park, H Best, JHH Chan, KES Ford, MJ Graham, VA Villar, ... The Astrophysical Journal 965 (2), 104, 2024 | 10 | 2024 |
| LSST Dark Energy Science Collaboration 2021 S Wagner-Carena, JW Park, S Birrer, PJ Marshall, A Roodman, ... ApJ 909, 187, 0 | 8 | |
| LSST Dark Energy Science Collaboration 2021 JW Park, S Wagner-Carena, S Birrer, PJ Marshall, JYY Lin, A Roodman ApJ 910, 39, 0 | 6 | |
| Chain of log-concave Markov chains S Saremi, JW Park, F Bach arXiv preprint arXiv:2305.19473, 2023 | 5 | 2023 |
| Multi-segment preserving sampling for deep manifold sampler D Berenberg, JH Lee, S Kelow, JW Park, A Watkins, V Gligorijević, ... arXiv preprint arXiv:2205.04259, 2022 | 5 | 2022 |
| Supsiam: Non-contrastive auxiliary loss for learning from molecular conformers M Maser, JW Park, JYY Lin, JH Lee, NC Frey, A Watkins arXiv preprint arXiv:2302.07754, 2023 | 4 | 2023 |
| Antibody domainbed: Out-of-distribution generalization in therapeutic protein design N Tagasovska, JW Park, M Kirchmeyer, NC Frey, AM Watkins, AA Ismail, ... arXiv preprint arXiv:2407.21028, 2024 | 3 | 2024 |
| Hierarchical inference of the lensing convergence from photometric catalogs with Bayesian graph neural networks JW Park, S Birrer, M Ueland, M Cranmer, A Agnello, S Wagner-Carena, ... The Astrophysical Journal 953 (2), 178, 2023 | 3 | 2023 |
| Inferring black hole properties from astronomical multivariate time series with Bayesian attentive neural processes JW Park, A Villar, Y Li, YF Jiang, S Ho, JYY Lin, PJ Marshall, A Roodman arXiv preprint arXiv:2106.01450, 2021 | 3 | 2021 |
| Blind biological sequence denoising with self-supervised set learning N Ng, JW Park, JH Lee, RL Kelly, S Ra, K Cho arXiv preprint arXiv:2309.01670, 2023 | 1 | 2023 |
| BOtied: Multi-objective Bayesian optimization with tied multivariate ranks JW Park, N Tagasovska, M Maser, S Ra, K Cho arXiv preprint arXiv:2306.00344, 2023 | 1 | 2023 |
Simon BirrerStony Brook UniversityVerified email at stonybrook.edu
