Willie Neiswanger
37 papers · 2014–2026 · 11 conferences · across top CS/AI conferences
Achievements
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Cross-Pollinator
(7)
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Dynamic Duo
(10)
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(36)
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Conferences
NIPS (8)
ICLR (7)
ICML (6)
AAAI (4)
AISTATS (4)
EMNLP (2)
JMLR (2)
ACL (1)
ALT (1)
CORL (1)
OSDI (1)
Top co-authors
Research topics
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
Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models
ACL 2026
TokenSmith: Streamlining Data Editing, Search, and Inspection for Large-Scale Language Model Training and Interpretability
EMNLP 2025
Efficient Evaluation of Multi-Task Robot Policies With Active Experiment Selection
CORL 2025
LiveBench: A Challenging, Contamination-Limited LLM Benchmark
ICLR 2025
DeLLMa: Decision Making Under Uncertainty with Large Language Models
ICLR 2025
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution
AAAI 2024
Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching
AAAI 2023
Near-optimal Policy Identification in Active Reinforcement Learning
ICLR 2023
Generative Modeling Helps Weak Supervision (and Vice Versa)
ICLR 2023
Making Scalable Meta Learning Practical
NIPS 2023
Importance-aware Co-teaching for Offline Model-based Optimization
NIPS 2023
Betty: An Automatic Differentiation Library for Multilevel Optimization
ICLR 2023
Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis
EMNLP 2022
Generalizing Bayesian Optimization with Decision-theoretic Entropies
NIPS 2022
Exploration via Planning for Information about the Optimal Trajectory
NIPS 2022
IS-Count: Large-Scale Object Counting from Satellite Images with Covariate-Based Importance Sampling
AAAI 2022
An Experimental Design Perspective on Model-Based Reinforcement Learning
ICLR 2022
Modular Conformal Calibration
ICML 2022
A General Recipe for Likelihood-free Bayesian Optimization
ICML 2022
Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information
ICML 2021
Uncertainty quantification using martingales for misspecified Gaussian processes
ALT 2021
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
AAAI 2021
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification
NIPS 2021
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
ICLR 2021
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning
OSDI 2021
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
JMLR 2020
A Study on Encodings for Neural Architecture Search
NIPS 2020
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations
AISTATS 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
Post-Inference Prior Swapping
ICML 2017
Performance Bounds for Graphical Record Linkage
AISTATS 2017
Generalized Pólya 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