Deblending and classifying astronomical sources with Mask R-CNN deep learning CJ Burke, PD Aleo, YC Chen, X Liu, JR Peterson, GH Sembroski, JYY Lin Monthly Notices of the Royal Astronomical Society 490 (3), 3952-3965, 2019 | 75 | 2019 |
A deep-learning approach for live anomaly detection of extragalactic transients VA Villar, M Cranmer, E Berger, G Contardo, S Ho, G Hosseinzadeh, ... The Astrophysical Journal Supplement Series 255 (2), 24, 2021 | 43 | 2021 |
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 | 39 | 2021 |
deeplenstronomy: A dataset simulation package for strong gravitational lensing R Morgan, B Nord, S Birrer, JYY Lin, J Poh arXiv preprint arXiv:2102.02830, 2021 | 16 | 2021 |
Galaxy morphological classification with efficient vision transformer JYY Lin, SM Liao, HJ Huang, WT Kuo, OHM Ou arXiv preprint arXiv:2110.01024, 2021 | 8 | 2021 |
Strong gravitational lensing parameter estimation with vision transformer KW Huang, GCF Chen, PW Chang, SC Lin, CJ Hsu, V Thengane, JYY Lin European Conference on Computer Vision, 143-153, 2022 | 5 | 2022 |
Learning Principle of Least Action with Reinforcement Learning Z Jin, JYY Lin, SF Li arXiv preprint arXiv:2011.11891, 2020 | 4 | 2020 |
Hunting for dark matter Subhalos in strong gravitational lensing with neural networks JYY Lin, H Yu, W Morningstar, J Peng, G Holder arXiv preprint arXiv:2010.12960, 2020 | 4 | 2020 |
Anomaly detection for multivariate time series of exotic supernovae VA Villar, M Cranmer, G Contardo, S Ho, JYY Lin arXiv preprint arXiv:2010.11194, 2020 | 4 | 2020 |
Gravitational lensing of the cosmic neutrino background JYY Lin, G Holder Journal of Cosmology and Astroparticle Physics 2020 (04), 054, 2020 | 4 | 2020 |
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 | 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 |
Feature Extraction on Synthetic Black Hole Images JYY Lin, GN Wong, BS Prather, CF Gammie arXiv preprint arXiv:2007.00794, 2020 | 3 | 2020 |
AGNet: weighing black holes with deep learning JYY Lin, S Pandya, D Pratap, X Liu, M Carrasco Kind, V Kindratenko Monthly Notices of the Royal Astronomical Society 518 (4), 4921-4929, 2023 | 2 | 2023 |
Agnet: Weighing black holes with machine learning JYY Lin, S Pandya, D Pratap, X Liu, MC Kind arXiv preprint arXiv:2011.15095, 2020 | 1 | 2020 |
Hunting for Dark Matter Subhalos in Strong Gravitational Lensing with Neural Networks J Yao-Yu Lin, H Yu, W Morningstar, J Peng, G Holder arXiv e-prints, arXiv: 2010.12960, 2020 | 1 | 2020 |
Impact of Gravitational Slingshot of Dark Matter on Galactic Halo Profiles P Chen, YS Duh, L Labun, YY Lin arXiv preprint arXiv:1412.2258, 2014 | 1 | 2014 |
MolSiam: Simple Siamese Self-supervised Representation Learning for Small Molecules JYY Lin, P Design, M Maser, N Frey, G Scalia, G gRED, O Mahmood, ... NeurIPS 2023 Workshop on New Frontiers of AI for Drug Discovery and Development, 2023 | | 2023 |
LenSiam: Self-Supervised Learning on Strong Gravitational Lens Images PW Chang, KW Huang, J Fagin, JHH Chan, JYY Lin arXiv preprint arXiv:2311.10100, 2023 | | 2023 |
Machine Learning application for astrophysics: A case study for black hole images and strong gravitational lensing JYY Lin, EHT Team APS March Meeting Abstracts 2023, M53. 001, 2023 | | 2023 |