Willie Neiswanger
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
29
Venues
9
Active years
2014–2026
Best venue rank
A*
Where they publish
Papers
29 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models. | Woody Haosheng Gan, Deqing Fu, Julian Asilis, Ollie Liu, Vatsal Sharan, Robin Jia, Willie Neiswanger |
| 2025 | EMNLP | TokenSmith: Streamlining Data Editing, Search, and Inspection for Large-Scale Language Model Training and Interpretability. | Mohammad Aflah Khan, Ameya Godbole, Johnny Tian-Zheng Wei, Ryan Yixiang Wang, James Flemings, Krishna P. Gummadi, Willie Neiswanger, Robin Jia |
| 2025 | ICLR | DeLLMa: Decision Making Under Uncertainty with Large Language Models. | Ollie Liu, Deqing Fu, Dani Yogatama, Willie Neiswanger |
| 2025 | ICLR | LiveBench: A Challenging, Contamination-Limited LLM Benchmark. | Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Sreemanti Dey, Shubh-Agrawal, Sandeep Singh Sandha, Siddartha V. Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum |
| 2024 | AAAI | Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution. | Tailin Wu, Willie Neiswanger, Hongtao Zheng, Stefano Ermon, Jure Leskovec |
| 2023 | AAAI | Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching. | Lantao Yu, Tianhe Yu, Jiaming Song, Willie Neiswanger, Stefano Ermon |
| 2023 | ICLR | Generative Modeling Helps Weak Supervision (and Vice Versa). | Benedikt Boecking, Nicholas Carl Roberts, Willie Neiswanger, Stefano Ermon, Frederic Sala, Artur Dubrawski |
| 2023 | ICLR | Betty: An Automatic Differentiation Library for Multilevel Optimization. | Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric P. Xing |
| 2023 | ICLR | Near-optimal Policy Identification in Active Reinforcement Learning. | Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic |
| 2022 | AAAI | IS-Count: Large-Scale Object Counting from Satellite Images with Covariate-Based Importance Sampling. | Chenlin Meng, Enci Liu, Willie Neiswanger, Jiaming Song, Marshall Burke, David B. Lobell, Stefano Ermon |
| 2022 | EMNLP | Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis. | Yuxin Xiao, Paul Pu Liang, Umang Bhatt, Willie Neiswanger, Ruslan Salakhutdinov, Louis-Philippe Morency |
| 2022 | ICLR | An Experimental Design Perspective on Model-Based Reinforcement Learning. | Viraj Mehta, Biswajit Paria, Jeff Schneider, Stefano Ermon, Willie Neiswanger |
| 2022 | ICML | Modular Conformal Calibration. | Charles Marx, Shengjia Zhao, Willie Neiswanger, Stefano Ermon |
| 2022 | ICML | A General Recipe for Likelihood-free Bayesian Optimization. | Jiaming Song, Lantao Yu, Willie Neiswanger, Stefano Ermon |
| 2021 | AAAI | BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search. | Colin White, Willie Neiswanger, Yash Savani |
| 2021 | ALT | Uncertainty quantification using martingales for misspecified Gaussian processes. | Willie Neiswanger, Aaditya Ramdas |
| 2021 | ICLR | Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling. | Benedikt Boecking, Willie Neiswanger, Eric P. Xing, Artur Dubrawski |
| 2021 | ICML | Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information. | Willie Neiswanger, Ke Alexander Wang, Stefano Ermon |
| 2021 | OSDI | Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. | Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing |
| 2020 | AISTATS | ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations. | Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabs Pczos, Jeff Schneider, Eric P. Xing |
| 2019 | ICML | Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments. | Kirthevasan Kandasamy, Willie Neiswanger, Reed Zhang, Akshay Krishnamurthy, Jeff Schneider, Barnabs Pczos |
| 2017 | AISTATS | Performance Bounds for Graphical Record Linkage. | Rebecca C. Steorts, Matt Barnes, Willie Neiswanger |
| 2017 | ICML | Post-Inference Prior Swapping. | Willie Neiswanger, Eric P. Xing |
| 2016 | ICML | Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms. | Yu-Xiang Wang, Veeranjaneyulu Sadhanala, Wei Dai, Willie Neiswanger, Suvrit Sra, Eric P. Xing |
| 2015 | AISTATS | Fast Function to Function Regression. | Junier B. Oliva, Willie Neiswanger, Barnabs Pczos, Eric P. Xing, Hy Trac, Shirley Ho, Jeff G. Schneider |
| 2014 | AISTATS | The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling. | Willie Neiswanger, Frank D. Wood, Eric P. Xing |
| 2014 | AISTATS | Fast Distribution To Real Regression. | Junier B. Oliva, Willie Neiswanger, Barnabs Pczos, Jeff G. Schneider, Eric P. Xing |
| 2014 | UAI | Modeling Citation Networks Using Latent Random Offsets. | Willie Neiswanger, Chong Wang, Qirong Ho, Eric P. Xing |
| 2014 | UAI | Asymptotically Exact, Embarrassingly Parallel MCMC. | Willie Neiswanger, Chong Wang, Eric P. Xing |