Willie Neiswanger

Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models ACL 2026 DeLLMa: Decision Making Under Uncertainty with Large Language Models ICLR 2025 Efficient Evaluation of Multi-Task Robot Policies With Active Experiment Selection CoRL 2025 LiveBench: A Challenging, Contamination-Limited LLM Benchmark ICLR 2025 TokenSmith: Streamlining Data Editing, Search, and Inspection for Large-Scale Language Model Training and Interpretability EMNLP 2025 Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution AAAI 2024 Betty: An Automatic Differentiation Library for Multilevel Optimization ICLR 2023 Generative Modeling Helps Weak Supervision (and Vice Versa) ICLR 2023 Importance-aware Co-teaching for Offline Model-based Optimization NeurIPS 2023 Making Scalable Meta Learning Practical NeurIPS 2023 Near-optimal Policy Identification in Active Reinforcement Learning ICLR 2023 Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching AAAI 2023 A General Recipe for Likelihood-free Bayesian Optimization ICML 2022 An Experimental Design Perspective on Model-Based Reinforcement Learning ICLR 2022 Exploration via Planning for Information about the Optimal Trajectory NeurIPS 2022 Generalizing Bayesian Optimization with Decision-theoretic Entropies NeurIPS 2022 IS-Count: Large-Scale Object Counting from Satellite Images with Covariate-Based Importance Sampling AAAI 2022 Modular Conformal Calibration ICML 2022 Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis EMNLP 2022 BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search AAAI 2021 Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information ICML 2021 Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification NeurIPS 2021 Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling ICLR 2021 Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning OSDI 2021 Uncertainty quantification using martingales for misspecified Gaussian processes ALT 2021 A Study on Encodings for Neural Architecture Search NeurIPS 2020 ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations AISTATS 2020 Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly JMLR 2020 Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments ICML 2019 Offline Contextual Bayesian Optimization NeurIPS 2019 Neural Architecture Search with Bayesian Optimisation and Optimal Transport NeurIPS 2018 Generalized Pólya Urn for Time-Varying Pitman-Yor Processes JMLR 2017 Performance Bounds for Graphical Record Linkage AISTATS 2017 Post-Inference Prior Swapping ICML 2017 Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms ICML 2016 Fast Distribution To Real Regression AISTATS 2014 The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling AISTATS 2014