Yeming Wen - RankMe

25 papers A* 6A 1Journal 16Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FronTalk: Benchmarking Front-End Development as Conversational Code Generation with Multi-Modal Feedback. CoRR Xueqing Wu, Zihan Xue, Da Yin, Shuyan Zhou, Kai-Wei Chang, Nanyun Peng, Yeming Wen
2024	A*	`conf`	Batched Low-Rank Adaptation of Foundation Models. ICLR Yeming Wen, Swarat Chaudhuri
2024	J	`jnl`	Grounding Data Science Code Generation with Input-Output Specifications. CoRR Yeming Wen, Pengcheng Yin, Kensen Shi, Henryk Michalewski, Swarat Chaudhuri, Alex Polozov
2024	A*	`conf`	Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models. NeurIPS Yeming Wen, Swarat Chaudhuri
2024	J	`jnl`	Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models. CoRR Yeming Wen, Swarat Chaudhuri
2023	J	`jnl`	A Language-Agent Approach to Formal Theorem-Proving. CoRR Amitayush Thakur, Yeming Wen, Swarat Chaudhuri
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	J	`jnl`	Batched Low-Rank Adaptation of Foundation Models. CoRR Yeming Wen, Swarat Chaudhuri
2023	—	`conf`	Natural Language to Code Generation in Interactive Data Science Notebooks. ACL (1) Pengcheng Yin, Wen-Ding Li, Kefan Xiao, Abhishek Rao, Yeming Wen, Kensen Shi, Joshua Howland, Paige Bailey, Michele Catasta, Henryk Michalewski, Oleksandr Polozov, Charles Sutton
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	J	`jnl`	Natural Language to Code Generation in Interactive Data Science Notebooks. CoRR Pengcheng Yin, Wen-Ding Li, Kefan Xiao, Abhishek Rao, Yeming Wen, Kensen Shi, Joshua Howland, Paige Bailey, Michele Catasta, Henryk Michalewski, Alex Polozov, Charles Sutton
2021	A*	`conf`	Combining Ensembles and Data Augmentation Can Harm Your Calibration. ICLR Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran
2021	A*	`conf`	Neural Program Generation Modulo Static Analysis. NeurIPS Rohan Mukherjee, Yeming Wen, Dipak Chaudhari, Thomas W. Reps, Swarat Chaudhuri, Christopher M. Jermaine
2021	J	`jnl`	Neural Program Generation Modulo Static Analysis. CoRR Rohan Mukherjee, Yeming Wen, Dipak Chaudhari, Thomas W. Reps, Swarat Chaudhuri, Chris Jermaine
2021	J	`jnl`	Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Z. Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran
2020	A	`conf`	An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise. AISTATS Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba
2020	J	`jnl`	BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning. CoRR Yeming Wen, Dustin Tran, Jimmy Ba
2020	A*	`conf`	BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning. ICLR Yeming Wen, Dustin Tran, Jimmy Ba
2020	J	`jnl`	Combining Ensembles and Data Augmentation can Harm your Calibration. CoRR Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran
2020	A*	`conf`	Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors. ICML Michael Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-An Ma, Jasper Snoek, Katherine A. Heller, Balaji Lakshminarayanan, Dustin Tran
2020	J	`jnl`	Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors. CoRR Michael W. Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-An Ma, Jasper Snoek, Katherine A. Heller, Balaji Lakshminarayanan, Dustin Tran
2019	J	`jnl`	Benchmarking Model-Based Reinforcement Learning. CoRR Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang, Yeming Wen, Eric D. Langlois, Shunshi Zhang, Guodong Zhang, Pieter Abbeel, Jimmy Ba
2019	J	`jnl`	Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise. CoRR Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba
2018	—	`conf`	Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. ICLR (Poster) Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse
2018	J	`jnl`	Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. CoRR Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse