← Authors

Willie Neiswanger

36 papers · 2014–2025 · 10 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (8) 🌍 Conference Polyglot (10) πŸƒ Academic Marathon (11) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (7) 🀝 Dynamic Duo (10) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (10) πŸ’Ž Century Club (36) ⚑ Prolific Year (7) πŸ—ƒοΈ Keyword Collector (139) πŸ”₯ Unstoppable (10)

Conferences

NIPS (8) ICLR (7) ICML (6) AAAI (4) AISTATS (4) EMNLP (2) JMLR (2) ALT (1) CORL (1) OSDI (1)

Top co-authors

Stefano Ermon (10) Jeff Schneider (8) Eric Xing (7) Kirthevasan Kandasamy (5) BarnabΓ‘s PΓ³czos (5) Eric P. Xing (4) Ian Char (4) Jiaming Song (3) Viraj Mehta (3) Lantao Yu (3)

Research topics

Deep Learning (1)

Keywords

bayesian optimization (8) gaussian process (5) uncertainty quantification (5) acquisition function (4) neural architecture search (4) bayesian inference (3) black-box optimization (3) bayesian nonparametrics (2) dirichlet process (2) architecture encoding (2) hyperparameter tuning (2) surrogate model (2) entropy search (2) importance sampling (2) optimal transport (2) posterior sampling (2) expected improvement (2) hyperparameter optimization (1) decision theory (1) density estimation (1)

Papers

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
Generative Modeling Helps Weak Supervision (and Vice Versa) ICLR 2023
Near-optimal Policy Identification in Active Reinforcement Learning ICLR 2023
Betty: An Automatic Differentiation Library for Multilevel Optimization ICLR 2023
Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching AAAI 2023
Making Scalable Meta Learning Practical NIPS 2023
Importance-aware Co-teaching for Offline Model-based Optimization NIPS 2023
A General Recipe for Likelihood-free Bayesian Optimization ICML 2022
Generalizing Bayesian Optimization with Decision-theoretic Entropies NIPS 2022
An Experimental Design Perspective on Model-Based Reinforcement Learning ICLR 2022
Exploration via Planning for Information about the Optimal Trajectory NIPS 2022
Modular Conformal Calibration ICML 2022
IS-Count: Large-Scale Object Counting from Satellite Images with Covariate-Based Importance Sampling AAAI 2022
Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis EMNLP 2022
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning OSDI 2021
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification NIPS 2021
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search AAAI 2021
Uncertainty quantification using martingales for misspecified Gaussian processes ALT 2021
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling ICLR 2021
Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information ICML 2021
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
A Study on Encodings for Neural Architecture Search NIPS 2020
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments ICML 2019
Offline Contextual Bayesian Optimization NIPS 2019
Neural Architecture Search with Bayesian Optimisation and Optimal Transport NIPS 2018
Performance Bounds for Graphical Record Linkage AISTATS 2017
Post-Inference Prior Swapping ICML 2017
Generalized PΓ³lya Urn for Time-Varying Pitman-Yor Processes JMLR 2017
Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms ICML 2016
The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling AISTATS 2014
Fast Distribution To Real Regression AISTATS 2014