← Authors

Arnaud Doucet

72 papers · 2007–2025 · 10 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (13) 🏃 Academic Marathon (18) 🌈 Renaissance Researcher (5) 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (10) 🗺️ Taxonomy Completionist (19) 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (8) 🏠 Conference Loyalist (26) 🤝 Dynamic Duo (16) 👑 Triple Crown 🌱 Topic Pioneer 🔬 Deep Specialist (20) 🏆 Keyword Champion (9) 🗃️ Keyword Collector (82) 💎 Century Club (72) 📈 Trend Setter ⚡ Prolific Year (12) 🔥 Unstoppable (12)

Conferences

NIPS (26) ICML (19) AISTATS (7) JMLR (6) ICLR (5) UAI (4) ALT (2) COLT (1) CORL (1) RSS (1)

Top co-authors

George Deligiannidis (16) Valentin De Bortoli (14) Yee Whye Teh (7) Yuyang Shi (5) Eugenio Clerico (5) Arthur Gretton (5) Andrew Campbell (5) Rob Cornish (5) Nando de Freitas (5) Yutian Chen (5)

Keywords

markov chain monte carlo (17) variational inference (11) diffusion model (9) sequential monte carlo (7) generative model (7) bayesian inference (7) particle filter (7) optimal transport (5) latent variable model (5) normalizing flow (5) variational autoencoder (4) importance sampling (4) state-space model (4) annealed importance sampling (4) marginal likelihood (4) posterior distribution (3) schrödinger bridge (3) generalization bound (3) density estimation (3) evidence lower bound (3)

Papers

Distributional Diffusion Models with Scoring Rules ICML 2025
Accelerated Diffusion Models via Speculative Sampling ICML 2025
Implicit Diffusion: Efficient optimization through stochastic sampling AISTATS 2025
Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts ICML 2025
Generalisation under gradient descent via deterministic PAC-Bayes ALT 2025
Score-Optimal Diffusion Schedules NIPS 2024
Simplified and Generalized Masked Diffusion for Discrete Data NIPS 2024
Particle Denoising Diffusion Sampler ICML 2024
Nearly $d$-Linear Convergence Bounds for Diffusion Models via Stochastic Localization ICLR 2024
Schrodinger Bridge Flow for Unpaired Data Translation NIPS 2024
Trans-Dimensional Generative Modeling via Jump Diffusion Models NIPS 2023
Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters NIPS 2023
Diffusion Schrödinger Bridge Matching NIPS 2023
SE(3) diffusion model with application to protein backbone generation ICML 2023
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC ICML 2023
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics JMLR 2023
Wide stochastic networks: Gaussian limit and PAC-Bayesian training ALT 2023
Denoising Diffusion Samplers ICLR 2023
A Unified Framework for U-Net Design and Analysis NIPS 2023
Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits NIPS 2023
On Instrumental Variable Regression for Deep Offline Policy Evaluation JMLR 2022
Learning Optimal Conformal Classifiers ICLR 2022
Importance Weighted Kernel Bayes’ Rule ICML 2022
Continual Repeated Annealed Flow Transport Monte Carlo ICML 2022
Conditional simulation using diffusion Schrödinger bridges UAI 2022
Mitigating statistical bias within differentially private synthetic data UAI 2022
Riemannian Score-Based Generative Modelling NIPS 2022
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs NIPS 2022
Score-Based Diffusion meets Annealed Importance Sampling NIPS 2022
A Continuous Time Framework for Discrete Denoising Models NIPS 2022
Conformal Off-Policy Prediction in Contextual Bandits NIPS 2022
Towards Learning Universal Hyperparameter Optimizers with Transformers NIPS 2022
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving CORL 2022
Conditionally Gaussian PAC-Bayes AISTATS 2022
Generative Models as Distributions of Functions AISTATS 2022
On PAC-Bayesian reconstruction guarantees for VAEs AISTATS 2022
Chained generalisation bounds COLT 2022
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting JMLR 2022
NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform NIPS 2021
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling NIPS 2021
Online Variational Filtering and Parameter Learning NIPS 2021
Stable ResNet AISTATS 2021
Robust Pruning at Initialization ICLR 2021
Learning Deep Features in Instrumental Variable Regression ICLR 2021
Annealed Flow Transport Monte Carlo ICML 2021
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport ICML 2021
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding ICML 2021
Monte Carlo Variational Auto-Encoders ICML 2021
Variational inference with continuously-indexed normalizing flows UAI 2021
Unbiased gradient estimation for variational auto-encoders using coupled Markov chains UAI 2021
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows ICML 2020
Modular Meta-Learning with Shrinkage NIPS 2020
On the Impact of the Activation function on Deep Neural Networks Training ICML 2019
Augmented Neural ODEs NIPS 2019
Unbiased Smoothing using Particle Independent Metropolis-Hastings AISTATS 2019
Bernoulli Race Particle Filters AISTATS 2019
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets ICML 2019
Replica Conditional Sequential Monte Carlo ICML 2019
Hamiltonian Variational Auto-Encoder NIPS 2018
Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling NIPS 2017
Filtering Variational Objectives NIPS 2017
Generalized Pólya Urn for Time-Varying Pitman-Yor Processes JMLR 2017
Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models JMLR 2017
On Markov chain Monte Carlo methods for tall data JMLR 2017
Interacting Particle Markov Chain Monte Carlo ICML 2016
Expectation Particle Belief Propagation NIPS 2015
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach ICML 2014
Fast Computation of Wasserstein Barycenters ICML 2014
Asynchronous Anytime Sequential Monte Carlo NIPS 2014
Bayesian Nonparametric Models on Decomposable Graphs NIPS 2009
Bayesian Policy Learning with Trans-Dimensional MCMC NIPS 2007
Active Policy Learning for Robot Planning and Exploration under Uncertainty RSS 2007