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2020 – today
- 2023
[i10]Michael Maser, Ji Won Park, Joshua Yao-Yu Lin, Jae Hyeon Lee, Nathan C. Frey, Andrew M. Watkins:
SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers. CoRR abs/2302.07754 (2023)- 2022
- [c2]Kuan-Wei Huang, Geoff Chih-Fan Chen, Po-Wen Chang, Sheng-Chieh Lin, Chia-Jung Hsu, Vishal Thengane, Joshua Yao-Yu Lin:
Strong Gravitational Lensing Parameter Estimation with Vision Transformer. ECCV Workshops (1) 2022: 143-153 - [i9]Kuan-Wei Huang, Geoff Chih-Fan Chen, Po-Wen Chang, Sheng-Chieh Lin, Chia-Jung Hsu, Vishal Thengane, Joshua Yao-Yu Lin:
Strong Gravitational Lensing Parameter Estimation with Vision Transformer. CoRR abs/2210.04143 (2022) - 2021
- [j1]Robert Morgan
, Brian Nord, Simon Birrer, Joshua Yao-Yu Lin, Jason Poh:
deeplenstronomy: A dataset simulation package for strong gravitational lensing. J. Open Source Softw. 6(58): 2854 (2021) - [c1]Zehao Jin, Joshua Yao-Yu Lin, Siao-Fong Li:
Learning the Principle of Least Action with Reinforcement Learning. AAAI Spring Symposium: MLPS 2021 - [i8]V. Ashley Villar, Miles D. Cranmer, Edo Berger, Gabriella Contardo, Shirley Ho, Griffin Hosseinzadeh, Joshua Yao-Yu Lin:
A Deep Learning Approach for Active Anomaly Detection of Extragalactic Transients. CoRR abs/2103.12102 (2021) - [i7]Ji Won Park, V. Ashley Villar, Yin Li, Yan-Fei Jiang, Shirley Ho, Joshua Yao-Yu Lin, Philip J. Marshall, Aaron Roodman:
Inferring Black Hole Properties from Astronomical Multivariate Time Series with Bayesian Attentive Neural Processes. CoRR abs/2106.01450 (2021) - [i6]Joshua Yao-Yu Lin, Sneh Pandya, Devanshi Pratap, Xin Liu, Matias Carrasco Kind, Volodymyr V. Kindratenko:
AGNet: Weighing Black Holes with Deep Learning. CoRR abs/2108.07749 (2021) - [i5]Joshua Yao-Yu Lin, Dominic W. Pesce, George N. Wong, Ajay Uppili Arasanipalai, Ben S. Prather, Charles F. Gammie:
VLBInet: Radio Interferometry Data Classification for EHT with Neural Networks. CoRR abs/2110.07185 (2021) - 2020
- [i4]V. Ashley Villar, Miles D. Cranmer, Gabriella Contardo, Shirley Ho, Joshua Yao-Yu Lin:
Anomaly Detection for Multivariate Time Series of Exotic Supernovae. CoRR abs/2010.11194 (2020) - [i3]Zehao Jin, Joshua Yao-Yu Lin, Siao-Fong Li:
Learning Principle of Least Action with Reinforcement Learning. CoRR abs/2011.11891 (2020) - [i2]Joshua Yao-Yu Lin, Sneh Pandya, Devanshi Pratap, Xin Liu, Matias Carrasco Kind:
AGNet: Weighing Black Holes with Machine Learning. CoRR abs/2011.15095 (2020) - [i1]Ji Won Park, Sebastian Wagner-Carena, Simon Birrer, Philip J. Marshall, Joshua Yao-Yu Lin, Aaron Roodman:
Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant. CoRR abs/2012.00042 (2020)
Coauthor Index
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