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Yeming Wen
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2020 – today
- 2024
- [c8]Yeming Wen, Swarat Chaudhuri:
Batched Low-Rank Adaptation of Foundation Models. ICLR 2024 - [i13]Yeming Wen, Pengcheng Yin, Kensen Shi, Henryk Michalewski, Swarat Chaudhuri, Alex Polozov:
Grounding Data Science Code Generation with Input-Output Specifications. CoRR abs/2402.08073 (2024) - 2023
- [j1]Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zachary Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan:
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. J. Mach. Learn. Res. 24: 42:1-42:63 (2023) - [c7]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:
Natural Language to Code Generation in Interactive Data Science Notebooks. ACL (1) 2023: 126-173 - [i12]Amitayush Thakur, Yeming Wen, Swarat Chaudhuri:
A Language-Agent Approach to Formal Theorem-Proving. CoRR abs/2310.04353 (2023) - [i11]Yeming Wen, Swarat Chaudhuri:
Batched Low-Rank Adaptation of Foundation Models. CoRR abs/2312.05677 (2023) - 2022
- [i10]Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zack Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan:
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. CoRR abs/2205.00403 (2022) - [i9]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:
Natural Language to Code Generation in Interactive Data Science Notebooks. CoRR abs/2212.09248 (2022) - 2021
- [c6]Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran:
Combining Ensembles and Data Augmentation Can Harm Your Calibration. ICLR 2021 - [c5]Rohan Mukherjee, Yeming Wen, Dipak Chaudhari, Thomas W. Reps, Swarat Chaudhuri, Christopher M. Jermaine:
Neural Program Generation Modulo Static Analysis. NeurIPS 2021: 18984-18996 - [i8]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:
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR abs/2106.04015 (2021) - [i7]Rohan Mukherjee, Yeming Wen, Dipak Chaudhari, Thomas W. Reps, Swarat Chaudhuri, Chris Jermaine:
Neural Program Generation Modulo Static Analysis. CoRR abs/2111.01633 (2021) - 2020
- [c4]Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba:
An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise. AISTATS 2020: 3621-3631 - [c3]Yeming Wen, Dustin Tran, Jimmy Ba:
BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning. ICLR 2020 - [c2]Michael Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-An Ma, Jasper Snoek, Katherine A. Heller, Balaji Lakshminarayanan, Dustin Tran:
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors. ICML 2020: 2782-2792 - [i6]Yeming Wen, Dustin Tran, Jimmy Ba:
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning. CoRR abs/2002.06715 (2020) - [i5]Michael W. Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-An Ma, Jasper Snoek, Katherine A. Heller, Balaji Lakshminarayanan, Dustin Tran:
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors. CoRR abs/2005.07186 (2020) - [i4]Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran:
Combining Ensembles and Data Augmentation can Harm your Calibration. CoRR abs/2010.09875 (2020)
2010 – 2019
- 2019
- [i3]Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba:
Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise. CoRR abs/1902.08234 (2019) - [i2]Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang, Yeming Wen, Eric D. Langlois, Shunshi Zhang, Guodong Zhang, Pieter Abbeel, Jimmy Ba:
Benchmarking Model-Based Reinforcement Learning. CoRR abs/1907.02057 (2019) - 2018
- [c1]Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse:
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. ICLR (Poster) 2018 - [i1]Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse:
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. CoRR abs/1803.04386 (2018)
Coauthor Index
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