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Jiayu Yao
Jiayu Yao
Gladstone Institutes
Verified email at gladstone.ucsf.edu - Homepage
Title
Cited by
Cited by
Year
Evaluating reinforcement learning algorithms in observational health settings
O Gottesman, F Johansson, J Meier, J Dent, D Lee, S Srinivasan, L Zhang, ...
arXiv preprint arXiv:1805.12298, 2018
1252018
Quality of uncertainty quantification for Bayesian neural network inference
J Yao, W Pan, S Ghosh, F Doshi-Velez
arXiv preprint arXiv:1906.09686, 2019
1192019
Normal/abnormal heart sound recordings classification using convolutional neural network
T Nilanon, J Yao, J Hao, S Purushotham, Y Liu
2016 computing in cardiology conference (CinC), 585-588, 2016
1122016
Structured variational learning of Bayesian neural networks with horseshoe priors
S Ghosh, J Yao, F Doshi-Velez
International Conference on Machine Learning, 1744-1753, 2018
782018
Model Selection in Bayesian Neural Networks via Horseshoe Priors.
S Ghosh, J Yao, F Doshi-Velez
J. Mach. Learn. Res. 20 (182), 1-46, 2019
762019
Power constrained bandits
J Yao, E Brunskill, W Pan, S Murphy, F Doshi-Velez
Machine Learning for Healthcare Conference, 209-259, 2021
312021
Direct policy transfer via hidden parameter markov decision processes
J Yao, T Killian, G Konidaris, F Doshi-Velez
LLARLA Workshop, FAIM 2018, 2018
312018
Output-constrained Bayesian neural networks
W Yang, L Lorch, MA Graule, S Srinivasan, A Suresh, J Yao, MF Pradier, ...
arXiv preprint arXiv:1905.06287, 2019
222019
Latent projection bnns: Avoiding weight-space pathologies by learning latent representations of neural network weights
MF Pradier, W Pan, J Yao, S Ghosh, F Doshi-Velez
Workshop on Bayesian Deep Learning, NIPS, 2018
112018
Projected BNNs: Avoiding weight-space pathologies by learning latent representations of neural network weights
MF Pradier, W Pan, J Yao, S Ghosh, F Doshi-Velez
arXiv preprint arXiv:1811.07006, 2018
92018
Li wei H
O Gottesman, F Johansson, J Meier, J Dent, D Lee, S Srinivasan, L Zhang, ...
Lehman, Matthieu Komorowski, Matthieu Komorowski, Aldo Faisal, Leo Anthony …, 1805
61805
Policy optimization with sparse global contrastive explanations
J Yao, S Parbhoo, W Pan, F Doshi-Velez
arXiv preprint arXiv:2207.06269, 2022
32022
An Empirical Analysis of the Advantages of Finite-vs Infinite-Width Bayesian Neural Networks
J Yao, Y Yacoby, B Coker, W Pan, F Doshi-Velez
arXiv preprint arXiv:2211.09184, 2022
22022
Performance bounds for model and policy transfer in hidden-parameter mdps
H Fu, J Yao, O Gottesman, F Doshi-Velez, G Konidaris
The Eleventh International Conference on Learning Representations, 2022
12022
Inverse Reinforcement Learning with Multiple Planning Horizons
J Yao, F Doshi-Velez, B Engelhardt
NeurIPS 2023 Workshop on Generalization in Planning, 2023
2023
Compositional Q-learning for electrolyte repletion with imbalanced patient sub-populations
A Mandyam, A Jones, J Yao, K Laudanski, BE Engelhardt
Machine Learning for Health (ML4H), 323-339, 2023
2023
Reinforcement Learning for Healthcare: From Model Development to Deployment
J Yao
2023
A Framework for the Evaluation of Clinical Time Series Models
M Gao, J Yao, R Henao
NeurIPS 2022 Workshop on Learning from Time Series for Health, 2022
2022
Success of Uncertainty-Aware Deep Models Depends on Data Manifold Geometry
M Penrod, H Termotto, V Reddy, J Yao, F Doshi-Velez, W Pan
arXiv preprint arXiv:2208.01705, 2022
2022
Development of a Machine Learning Model for Early Detection of Pediatric Sepsis
L Tang, W Ratliff, M Sendak, M Gao, M Nichols, M Revoir, F Yashar, J Yao, ...
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