Frank Wood

Constrained Generative Modeling with Manually Bridged Diffusion Models AAAI 2025 Towards a Mechanistic Explanation of Diffusion Model Generalization ICML 2025 All-in-one simulation-based inference ICML 2024 Don’t be so Negative! Score-based Generative Modeling with Oracle-assisted Guidance ICML 2024 Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning ICML 2024 Nearest Neighbour Score Estimators for Diffusion Generative Models ICML 2024 A Diffusion-Model of Joint Interactive Navigation NeurIPS 2023 Critic Sequential Monte Carlo ICLR 2023 Graphically Structured Diffusion Models ICML 2023 Uncertain Evidence in Probabilistic Models and Stochastic Simulators ICML 2023 Amortized Rejection Sampling in Universal Probabilistic Programming AISTATS 2022 BayesPCN: A Continually Learnable Predictive Coding Associative Memory NeurIPS 2022 Conditional Image Generation by Conditioning Variational Auto-Encoders ICLR 2022 Enhancing Few-Shot Image Classification With Unlabelled Examples WACV 2022 Flexible Diffusion Modeling of Long Videos NeurIPS 2022 Probabilistic surrogate networks for simulators with unbounded randomness UAI 2022 q-Paths: Generalizing the geometric annealing path using power means UAI 2021 Robust Asymmetric Learning in POMDPs ICML 2021 Sequential core-set Monte Carlo UAI 2021 All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference ICML 2020 Coping With Simulators That Don’t Always Return AISTATS 2020 Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective NeurIPS 2020 Improved Few-Shot Visual Classification CVPR 2020 Semi-supervised Sequential Generative Models UAI 2020 Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical Models AISTATS 2020 Target–Aware Bayesian Inference: How to Beat Optimal Conventional Estimators JMLR 2020 Amortized Monte Carlo Integration ICML 2019 Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model NeurIPS 2019 LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models AISTATS 2019 Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow UAI 2019 The Thermodynamic Variational Objective NeurIPS 2019 Auto-Encoding Sequential Monte Carlo ICLR 2018 Bayesian Distributed Stochastic Gradient Descent NeurIPS 2018 Deep Variational Reinforcement Learning for POMDPs ICML 2018 Faithful Inversion of Generative Models for Effective Amortized Inference NeurIPS 2018 Online Learning Rate Adaptation with Hypergradient Descent ICLR 2018 On Nesting Monte Carlo Estimators ICML 2018 Tighter Variational Bounds are Not Necessarily Better ICML 2018 Generalized Pólya Urn for Time-Varying Pitman-Yor Processes JMLR 2017 Inference Compilation and Universal Probabilistic Programming AISTATS 2017 Learning Disentangled Representations with Semi-Supervised Deep Generative Models NeurIPS 2017 Bayesian Optimization for Probabilistic Programs NeurIPS 2016 Black-Box Policy Search with Probabilistic Programs AISTATS 2016 Inference Networks for Sequential Monte Carlo in Graphical Models ICML 2016 Interacting Particle Markov Chain Monte Carlo ICML 2016 Particle Gibbs with Ancestor Sampling for Probabilistic Programs AISTATS 2015 A Compilation Target for Probabilistic Programming Languages ICML 2014 A New Approach to Probabilistic Programming Inference AISTATS 2014 Asynchronous Anytime Sequential Monte Carlo NeurIPS 2014 The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling AISTATS 2014 A Joint Learning Model of Word Segmentation, Lexical Acquisition, and Phonetic Variability EMNLP 2013 Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data ICML 2013 Low rank continuous-space graphical models AISTATS 2012 Discussion of “The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling” AISTATS 2011 Hierarchically Supervised Latent Dirichlet Allocation NeurIPS 2011 Probabilistic Deterministic Infinite Automata NeurIPS 2010 Characterizing neural dependencies with copula models NeurIPS 2008 Dependent Dirichlet Process Spike Sorting NeurIPS 2008 Particle Filtering for Nonparametric Bayesian Matrix Factorization NeurIPS 2006 A Hierarchical Nonparametric Bayesian Approach to Statistical Language Model Domain Adaptation AISTATS 2005