Anomaly Detection for Multivariate Time Series of Exotic Supernovae. - V. Ashley Villar; Miles D. Cranmer; Gabriella Contardo; Shirley Ho; Joshua Yao-Yu Lin (CoRR, 2020)

AGNet: Weighing Black Holes with Machine Learning. - Joshua Yao-Yu Lin; Sneh Pandya; Devanshi Pratap; Xin Liu; Matias Carrasco Kind (CoRR, 2020)

Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant. - Ji Won Park; Sebastian Wagner-Carena; Simon Birrer; Philip J. Marshall; Joshua Yao-Yu Lin; Aaron Roodman (CoRR, 2020)

Learning the Principle of Least Action with Reinforcement Learning. - Zehao Jin; Joshua Yao-Yu Lin; Siao-Fong Li (AAAI Spring Symposium: MLPS, 2021)

A Deep Learning Approach for Active Anomaly Detection of Extragalactic Transients. - V. Ashley Villar; Miles D. Cranmer; Edo Berger; Gabriella Contardo; Shirley Ho; Griffin Hosseinzadeh; Joshua Yao-Yu Lin (CoRR, 2021)

Inferring Black Hole Properties from Astronomical Multivariate Time Series with Bayesian Attentive Neural Processes. - Ji Won Park; V. Ashley Villar; Yin Li 009; Yan-Fei Jiang; Shirley Ho; Joshua Yao-Yu Lin; Philip J. Marshall; Aaron Roodman (CoRR, 2021)

AGNet: Weighing Black Holes with Deep Learning. - Joshua Yao-Yu Lin; Sneh Pandya; Devanshi Pratap; Xin Liu; Matias Carrasco Kind; Volodymyr V. Kindratenko (CoRR, 2021)

VLBInet: Radio Interferometry Data Classification for EHT with Neural Networks. - Joshua Yao-Yu Lin; Dominic W. Pesce; George N. Wong; Ajay Uppili Arasanipalai; Ben S. Prather; Charles F. Gammie (CoRR, 2021)

deeplenstronomy: A dataset simulation package for strong gravitational lensing. - Robert Morgan; Brian Nord; Simon Birrer; Joshua Yao-Yu Lin; Jason Poh (J. Open Source Softw., 2021)

Strong Gravitational Lensing Parameter Estimation with Vision Transformer. - Kuan-Wei Huang; Geoff Chih-Fan Chen; Po-Wen Chang; Sheng-Chieh Lin; Chia-Jung Hsu; Vishal Thengane; Joshua Yao-Yu Lin (ECCV Workshops (1), 2022)

SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers. - Michael Maser; Ji Won Park; Joshua Yao-Yu Lin; Jae Hyeon Lee; Nathan C. Frey; Andrew M. Watkins (CoRR, 2023)