Jeremiah Zhe Liu

21 papers A* 5B 1Misc 1Journal 13Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	RRM: Robust Reward Model Training Mitigates Reward Hacking. ICLR Tianqi Liu, Wei Xiong, Jie Ren, Lichang Chen, Junru Wu, Rishabh Joshi, Yang Gao, Jiaming Shen, Zhen Qin, Tianhe Yu, Daniel Sohn, Anastasia Makarova, Jeremiah Zhe Liu, Yuan Liu, Bilal Piot, Abe Ittycheriah, Aviral Kumar, Mohammad Saleh
2023	J	`jnl`	A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. J. Mach. Learn. Res. Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zachary Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan
2023	A*	`conf`	A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models. ICML James Urquhart Allingham, Jie Ren, Michael W. Dusenberry, Xiuye Gu, Yin Cui, Dustin Tran, Jeremiah Zhe Liu, Balaji Lakshminarayanan
2023	J	`jnl`	A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models. CoRR James Urquhart Allingham, Jie Ren, Michael W. Dusenberry, Jeremiah Zhe Liu, Xiuye Gu, Yin Cui, Dustin Tran, Balaji Lakshminarayanan
2023	A*	`conf`	On Compositional Uncertainty Quantification for Seq2seq Graph Parsing. ICLR Zi Lin, Du Phan, Panupong Pasupat, Jeremiah Zhe Liu, Jingbo Shang
2023	A*	`conf`	Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play. ICLR Jeremiah Zhe Liu, Krishnamurthy (Dj) Dvijotham, Jihyeon Lee, Quan Yuan, Balaji Lakshminarayanan, Deepak Ramachandran
2023	J	`jnl`	Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play. CoRR Jeremiah Zhe Liu, Krishnamurthy (Dj) Dvijotham, Jihyeon Lee, Quan Yuan, Martin Strobel, Balaji Lakshminarayanan, Deepak Ramachandran
2022	J	`jnl`	A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. CoRR Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zack Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan
2022	B	`conf`	Bayesian Nonparametric Model Averaging Using Scalable Gaussian Process Representations. IEEE Big Data John W. Paisley, Sebastian Rowland, Jeremiah Zhe Liu, Brent A. Coull, Marianthi-Anna Kioumourtzoglou
2022	J	`jnl`	Deep Classifiers with Label Noise Modeling and Distance Awareness. Trans. Mach. Learn. Res. Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Zhe Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
2022	—	`conf`	Towards Collaborative Neural-Symbolic Graph Semantic Parsing via Uncertainty. ACL (Findings) Zi Lin, Jeremiah Zhe Liu, Jingbo Shang
2022	J	`jnl`	Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees. CoRR Wenying Deng, Beau Coker, Jeremiah Zhe Liu, Brent A. Coull
2021	A*	`conf`	Training independent subnetworks for robust prediction. ICLR Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Mingbo Dai, Dustin Tran
2020	J	`jnl`	Pruning Redundant Mappings in Transformer Models via Spectral-Normalized Identity Prior. CoRR Zi Lin, Jeremiah Zhe Liu, Zi Yang, Nan Hua, Dan Roth
2020	J	`jnl`	Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness. CoRR Jeremiah Zhe Liu, Zi Lin, Shreyas Padhy, Dustin Tran, Tania Bedrax-Weiss, Balaji Lakshminarayanan
2020	J	`jnl`	Training independent subnetworks for robust prediction. CoRR Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew M. Dai, Dustin Tran
2019	J	`jnl`	Accurate Uncertainty Estimation and Decomposition in Ensemble Learning. CoRR Jeremiah Zhe Liu, John W. Paisley, Marianthi-Anna Kioumourtzoglou, Brent A. Coull
2019	J	`jnl`	Gaussian Process Regression and Classification under Mathematical Constraints with Learning Guarantees. CoRR Jeremiah Zhe Liu
2019	Misc	`conf`	Personalized treatment for type 2 diabetes using weighted k-nearest neighbors. AMIA Wenyu Song, Linying Zhang, Emily Gill, Jeremiah Zhe Liu, Adam Wright
2019	J	`jnl`	Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon. CoRR Jeremiah Zhe Liu
2018	J	`jnl`	Adaptive and Calibrated Ensemble Learning with Dependent Tail-free Process. CoRR Jeremiah Zhe Liu, John W. Paisley, Marianthi-Anna Kioumourtzoglou, Brent A. Coull