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Tim G. J. Rudner

29 papers · 2019–2025 · 8 venues · across top CS/AI venues

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Achievements

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+11 more ↓ πŸ—ΊοΈ Taxonomy Completionist (55) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
πŸ‘₯ Mega-Team Β· Squad πŸ”¬ Deep Specialist (13) πŸ‘‘ Triple Crown πŸ† Grand Slam ⚑ Prolific Year Β· Productive πŸ”₯ Unstoppable Β· Bronze ❓ The Questioner (3) πŸ’Ž Century Club Β· Bronze πŸš€ Conference Pioneer 🌈 Renaissance Researcher (7) πŸ—ƒοΈ Keyword Collector (134)

Venues

ICML (10) NeurIPS (9) AISTATS (4) EMNLP (2) AAAI (1) CLeaR (1) ICLR (1) NAACL (1)

Top co-authors

Yarin Gal (9) Andrew Gordon Wilson (7) Yee Whye Teh (5) Andrew G Wilson (3) Shikai Qiu (3) Yucen Lily Li (3) Ravid Shwartz-Ziv (2) Sanyam Kapoor (2) Arman Cohan (2) Gunshi Gupta (2)

Research topics

Machine Learning (21) Artificial Intelligence (19) Deep Learning (16) Optimization & Theory (15) Core AI (10) Models (10) Bayesian & Probabilistic (9) Learning Types Β· Deep Learning (7) Learning Types Β· Machine Learning (6) Application Areas (5) Reinforcement Learning (4) Methods (4) Natural Language Processing (3) Core Methods (3) Computer Vision (2)

Keywords

bayesian inference (5) variational inference (5) reinforcement learning (3) bayesian neural network (3) representation learning (3) neural network (3) active learning (2) drug discovery (2) deep gaussian process (2) probabilistic modeling (2) continual learning (2) vision-language model (2) bayesian optimization (2) generalization bound (2) approximate inference (2) covariate shift (2) self-supervised learning (2) uncertainty quantification (2) protein design (2) language model (2)

Papers

Can Transformers Learn Full Bayesian Inference in Context? ICML 2025 Fine-Tuning with Uncertainty-Aware Priors Makes Vision and Language Foundation Models More Reliable AISTATS 2025 Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds AISTATS 2025 Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization AISTATS 2025 MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs EMNLP 2025 Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection ICML 2025 SCIURus: Shared Circuits for Interpretable Uncertainty Representations in Language Models NAACL 2025 Simple Factuality Probes Detect Hallucinations in Long-Form Natural Language Generation EMNLP 2025 A Study of Bayesian Neural Network Surrogates for Bayesian Optimization ICLR 2024 Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design ICML 2024 Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors AISTATS 2024 Non-Vacuous Generalization Bounds for Large Language Models ICML 2024 Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI ICML 2024 Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control NeurIPS 2024 An Information Theory Perspective on Variance-Invariance-Covariance Regularization NeurIPS 2023 Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? CLeaR 2023 Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions ICML 2023 Function-Space Regularization in Neural Networks: A Probabilistic Perspective ICML 2023 Protein Design with Guided Discrete Diffusion NeurIPS 2023 Should We Learn Most Likely Functions or Parameters? NeurIPS 2023 Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution NeurIPS 2023 Continual Learning via Sequential Function-Space Variational Inference ICML 2022 Tractable Function-Space Variational Inference in Bayesian Neural Networks NeurIPS 2022 On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations NeurIPS 2021 On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes ICML 2021 Outcome-Driven Reinforcement Learning via Variational Inference NeurIPS 2021 Inter-domain Deep Gaussian Processes ICML 2020 Multi3Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery AAAI 2019 VIREL: A Variational Inference Framework for Reinforcement Learning NeurIPS 2019