Wen, Yeming

12 publications

ICLR 2024 Batched Low-Rank Adaptation of Foundation Models Yeming Wen, Swarat Chaudhuri

NeurIPS 2024 Synthesize, Partition, Then Adapt: Eliciting Diverse Samples from Foundation Models Yeming Wen, Swarat Chaudhuri

NeurIPSW 2023 A Language-Agent Approach to Formal Theorem-Proving Amitayush Thakur, Yeming Wen, Swarat Chaudhuri

JMLR 2023 A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zachary Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan

NeurIPSW 2023 Batched Low-Rank Adaptation of Foundation Models Yeming Wen, Swarat Chaudhuri

NeurIPSW 2023 Grounding Code Generation with Input-Output Specifications Yeming Wen, Pengcheng Yin, Kensen Shi, Henryk Michalewski, Swarat Chaudhuri, Alex Polozov

ICLR 2021 Combining Ensembles and Data Augmentation Can Harm Your Calibration Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran

NeurIPS 2021 Neural Program Generation Modulo Static Analysis Rohan Mukherjee, Yeming Wen, Dipak Chaudhari, Thomas Reps, Swarat Chaudhuri, Christopher Jermaine

AISTATS 2020 An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba

ICLR 2020 BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning Yeming Wen, Dustin Tran, Jimmy Ba

ICML 2020 Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors Michael Dusenberry, Ghassen Jerfel, Yeming Wen, Yian Ma, Jasper Snoek, Katherine Heller, Balaji Lakshminarayanan, Dustin Tran

ICLR 2018 Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger Grosse