Arnaud Doucet

ORCID

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 151

Top Venues

Publications

Soham De, Samuel L. Smith, Anushan Fernando, Aleksandar Botev, George-Cristian Muraru, Albert Gu, Ruba Haroun, Leonard Berrada, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, Arnaud Doucet, David Budden, Yee Whye Teh, Razvan Pascanu, Nando de Freitas, Caglar Gulcehre
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. CoRR (2024)
Jiaxin Shi, Kehang Han, Zhe Wang, Arnaud Doucet, Michalis K. Titsias
Simplified and Generalized Masked Diffusion for Discrete Data. CoRR (2024)
Valentin De Bortoli, Michael J. Hutchinson, Peter Wirnsberger, Arnaud Doucet
Target Score Matching. CoRR (2024)
Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet
Implicit Diffusion: Efficient Optimization through Stochastic Sampling. CoRR (2024)
Aleksandar Botev, Soham De, Samuel L. Smith, Anushan Fernando, George-Cristian Muraru, Ruba Haroun, Leonard Berrada, Razvan Pascanu, Pier Giuseppe Sessa, Robert Dadashi, Léonard Hussenot, Johan Ferret, Sertan Girgin, Olivier Bachem, Alek Andreev, Kathleen Kenealy, Thomas Mesnard, Cassidy Hardin, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Sanjay Kale, Juliette Love, Pouya Tafti, Armand Joulin, Noah Fiedel, Evan Senter, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, David Budden, Arnaud Doucet, Sharad Vikram, Adam Paszke, Trevor Gale, Sebastian Borgeaud, Charlie Chen, Andy Brock, Antonia Paterson, Jenny Brennan, Meg Risdal, Raj Gundluru, Nesh Devanathan, Paul Mooney, Nilay Chauhan, Phil Culliton, Luiz GUStavo Martins, Elisa Bandy, David Huntsperger, Glenn Cameron, Arthur Zucker, Tris Warkentin, Ludovic Peran, Minh Giang, Zoubin Ghahramani, Clément Farabet, Koray Kavukcuoglu, Demis Hassabis, Raia Hadsell, Yee Whye Teh, Nando de Frietas
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. CoRR (2024)
Angus Phillips, Hai-Dang Dau, Michael John Hutchinson, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
Particle Denoising Diffusion Sampler. CoRR (2024)
Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis
Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization. ICLR (2024)
Joe Benton, George Deligiannidis, Arnaud Doucet
Error Bounds for Flow Matching Methods. Trans. Mach. Learn. Res. 2024 (2024)
Yasin Abbasi-Yadkori, Ilja Kuzborskij, David Stutz, András György, Adam Fisch, Arnaud Doucet, Iuliya Beloshapka, Wei-Hung Weng, Yao-Yuan Yang, Csaba Szepesvári, Ali Taylan Cemgil, Nenad Tomasev
Mitigating LLM Hallucinations via Conformal Abstention. CoRR (2024)
Francisco Vargas, Will Sussman Grathwohl, Arnaud Doucet
Denoising Diffusion Samplers. ICLR (2023)
Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis
Linear Convergence Bounds for Diffusion Models via Stochastic Localization. CoRR (2023)
Eugenio Clerico, George Deligiannidis, Arnaud Doucet
Wide stochastic networks: Gaussian limit and PAC-Bayesian training. ALT (2023)
Muhammad Faaiz Taufiq, Arnaud Doucet, Rob Cornish, Jean-Francois Ton
Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits. CoRR (2023)
Rob Cornish, Muhammad Faaiz Taufiq, Arnaud Doucet, Chris Holmes
Causal Falsification of Digital Twins. CoRR (2023)
Andrew Campbell, William Harvey, Christian Weilbach, Valentin De Bortoli, Thomas Rainforth, Arnaud Doucet
Trans-Dimensional Generative Modeling via Jump Diffusion Models. NeurIPS (2023)
David Stutz, Abhijit Guha Roy, Tatiana Matejovicova, Patricia Strachan, Ali Taylan Cemgil, Arnaud Doucet
Conformal prediction under ambiguous ground truth. Trans. Mach. Learn. Res. 2023 (2023)
Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. CoRR (2023)
Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Grathwohl
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. CoRR (2023)
David Stutz, Abhijit Guha Roy, Tatiana Matejovicova, Patricia Strachan, Ali Taylan Cemgil, Arnaud Doucet
Conformal prediction under ambiguous ground truth. CoRR (2023)
Christopher Williams, Fabian Falck, George Deligiannidis, Chris C. Holmes, Arnaud Doucet, Saifuddin Syed
A Unified Framework for U-Net Design and Analysis. NeurIPS (2023)
Muhammad Faaiz Taufiq, Arnaud Doucet, Rob Cornish, Jean-Francois Ton
Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits. NeurIPS (2023)
Çaglar Gülçehre, Tom Le Paine, Srivatsan Srinivasan, Ksenia Konyushkova, Lotte Weerts, Abhishek Sharma, Aditya Siddhant, Alex Ahern, Miaosen Wang, Chenjie Gu, Wolfgang Macherey, Arnaud Doucet, Orhan Firat, Nando de Freitas
Reinforced Self-Training (ReST) for Language Modeling. CoRR (2023)
Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola
SE(3) diffusion model with application to protein backbone generation. ICML (2023)
Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Sussman Grathwohl
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. ICML (2023)
David Stutz, Ali Taylan Cemgil, Abhijit Guha Roy, Tatiana Matejovicova, Melih Barsbey, Patricia Strachan, Mike Schaekermann, Jan Freyberg, Rajeev Rikhye, Beverly Freeman, Javier Perez Matos, Umesh Telang, Dale R. Webster, Yuan Liu, Gregory S. Corrado, Yossi Matias, Pushmeet Kohli, Yun Liu, Arnaud Doucet, Alan Karthikesalingam
Evaluating AI systems under uncertain ground truth: a case study in dermatology. CoRR (2023)
Yuyang Shi, Valentin De Bortoli, Andrew Campbell, Arnaud Doucet
Diffusion Schrödinger Bridge Matching. NeurIPS (2023)
Maxence Noble, Valentin De Bortoli, Arnaud Doucet, Alain Durmus
Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters. CoRR (2023)
Francisco Vargas, Will Grathwohl, Arnaud Doucet
Denoising Diffusion Samplers. CoRR (2023)
Andrew Campbell, William Harvey, Christian Weilbach, Valentin De Bortoli, Tom Rainforth, Arnaud Doucet
Trans-Dimensional Generative Modeling via Jump Diffusion Models. CoRR (2023)
Christopher Williams, Fabian Falck, George Deligiannidis, Chris C. Holmes, Arnaud Doucet, Saifuddin Syed
A Unified Framework for U-Net Design and Analysis. CoRR (2023)
Joe Benton, George Deligiannidis, Arnaud Doucet
Error Bounds for Flow Matching Methods. CoRR (2023)
Yuyang Shi, Valentin De Bortoli, Andrew Campbell, Arnaud Doucet
Diffusion Schrödinger Bridge Matching. CoRR (2023)
Kamélia Daudel, Joe Benton, Yuyang Shi, Arnaud Doucet
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics. J. Mach. Learn. Res. 24 (2023)
Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola
SE(3) diffusion model with application to protein backbone generation. CoRR (2023)
Marin Vlastelica, Tatiana Lopez-Guevara, Kelsey R. Allen, Peter W. Battaglia, Arnaud Doucet, Kimberly L. Stachenfeld
Diffusion Generative Inverse Design. CoRR (2023)
Maxence Noble, Valentin De Bortoli, Arnaud Doucet, Alain Durmus
Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters. NeurIPS (2023)
Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet
On Instrumental Variable Regression for Deep Offline Policy Evaluation. J. Mach. Learn. Res. 23 (2022)
Arnaud Doucet, Will Grathwohl, Alexander G. de G. Matthews, Heiko Strathmann
Score-Based Diffusion meets Annealed Importance Sampling. CoRR (2022)
Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
Conditional simulation using diffusion Schrödinger bridges. UAI (2022)
Andrew Campbell, Joe Benton, Valentin De Bortoli, Tom Rainforth, George Deligiannidis, Arnaud Doucet
A Continuous Time Framework for Discrete Denoising Models. CoRR (2022)
Liyuan Xu, Yutian Chen, Arnaud Doucet, Arthur Gretton
Importance Weighting Approach in Kernel Bayes' Rule. CoRR (2022)
Badr-Eddine Chérief-Abdellatif, Yuyang Shi, Arnaud Doucet, Benjamin Guedj
On PAC-Bayesian reconstruction guarantees for VAEs. AISTATS (2022)
Liyuan Xu, Yutian Chen, Arnaud Doucet, Arthur Gretton
Importance Weighted Kernel Bayes' Rule. ICML (2022)
Eugenio Clerico, George Deligiannidis, Benjamin Guedj, Arnaud Doucet
A PAC-Bayes bound for deterministic classifiers. CoRR (2022)
Muhammad Faaiz Taufiq, Jean-Francois Ton, Robert Cornish, Yee Whye Teh, Arnaud Doucet
Conformal Off-Policy Prediction in Contextual Bandits. CoRR (2022)
Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matthew Hoffman, Razvan Pascanu, Arnaud Doucet
An empirical study of implicit regularization in deep offline RL. Trans. Mach. Learn. Res. 2022 (2022)
Maxime Vono, Daniel Paulin, Arnaud Doucet
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting. J. Mach. Learn. Res. 23 (2022)
Eugenio Clerico, George Deligiannidis, Arnaud Doucet
Conditionally Gaussian PAC-Bayes. AISTATS (2022)
James Thornton, Michael Hutchinson, Emile Mathieu, Valentin De Bortoli, Yee Whye Teh, Arnaud Doucet
Riemannian Diffusion Schrödinger Bridge. CoRR (2022)
Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Qiuyi Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas
Towards Learning Universal Hyperparameter Optimizers with Transformers. CoRR (2022)
Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H. Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, Curtis Hawthorne, Rémi Leblond, Will Grathwohl, Jonas Adler
Continuous diffusion for categorical data. CoRR (2022)
Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. NeurIPS (2022)
Emilien Dupont, Yee Whye Teh, Arnaud Doucet
Generative Models as Distributions of Functions. AISTATS (2022)
Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet
COIN++: Data Agnostic Neural Compression. CoRR (2022)
Muhammad Faaiz Taufiq, Jean-Francois Ton, Rob Cornish, Yee Whye Teh, Arnaud Doucet
Conformal Off-Policy Prediction in Contextual Bandits. NeurIPS (2022)
Kamélia Daudel, Joe Benton, Yuyang Shi, Arnaud Doucet
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics. CoRR (2022)
Andrew Campbell, Joe Benton, Valentin De Bortoli, Thomas Rainforth, George Deligiannidis, Arnaud Doucet
A Continuous Time Framework for Discrete Denoising Models. NeurIPS (2022)
Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
Conditional Simulation Using Diffusion Schrödinger Bridges. CoRR (2022)
Valentin De Bortoli, Emile Mathieu, Michael Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet
Riemannian Score-Based Generative Modeling. CoRR (2022)
Francesca R. Crucinio, Valentin De Bortoli, Arnaud Doucet, Adam M. Johansen
Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows. CoRR (2022)
Arnaud Doucet, Will Grathwohl, Alexander G. de G. Matthews, Heiko Strathmann
Score-Based Diffusion meets Annealed Importance Sampling. NeurIPS (2022)
Alexander G. de G. Matthews, Michael Arbel, Danilo Jimenez Rezende, Arnaud Doucet
Continual Repeated Annealed Flow Transport Monte Carlo. ICML (2022)
Angus Phillips, Thomas Seror, Michael Hutchinson, Valentin De Bortoli, Arnaud Doucet, Emile Mathieu
Spectral Diffusion Processes. CoRR (2022)
Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Richard Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas
Towards Learning Universal Hyperparameter Optimizers with Transformers. NeurIPS (2022)
Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matt Hoffman, Razvan Pascanu, Arnaud Doucet
An Empirical Study of Implicit Regularization in Deep Offline RL. CoRR (2022)
Amitis Shidani, George Deligiannidis, Arnaud Doucet
Ranking in Contextual Multi-Armed Bandits. CoRR (2022)
Badr-Eddine Chérief-Abdellatif, Yuyang Shi, Arnaud Doucet, Benjamin Guedj
On PAC-Bayesian reconstruction guarantees for VAEs. CoRR (2022)
Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet
COIN++: Neural Compression Across Modalities. Trans. Mach. Learn. Res. 2022 (2022)
Angad Singh, Omar Makhlouf, Maximilian Igl, João V. Messias, Arnaud Doucet, Shimon Whiteson
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving. CoRR (2022)
David Stutz, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet
Learning Optimal Conformal Classifiers. ICLR (2022)
Angad Singh, Omar Makhlouf, Maximilian Igl, João Messias, Arnaud Doucet, Shimon Whiteson
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving. CoRL (2022)
Pierre H. Richemond, Sander Dieleman, Arnaud Doucet
Categorical SDEs with Simplex Diffusion. CoRR (2022)
Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes
Mitigating statistical bias within differentially private synthetic data. UAI (2022)
Eugenio Clerico, Amitis Shidani, George Deligiannidis, Arnaud Doucet
Chained Generalisation Bounds. CoRR (2022)
Alexander G. de G. Matthews, Michael Arbel, Danilo J. Rezende, Arnaud Doucet
Continual Repeated Annealed Flow Transport Monte Carlo. CoRR (2022)
Pierre Glaser, Michael Arbel, Arnaud Doucet, Arthur Gretton
Maximum Likelihood Learning of Energy-Based Models for Simulation-Based Inference. CoRR (2022)
Eugenio Clerico, Amitis Shidani, George Deligiannidis, Arnaud Doucet
Chained generalisation bounds. COLT (2022)
Joe Benton, Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
From Denoising Diffusions to Denoising Markov Models. CoRR (2022)
Valentin De Bortoli, Emile Mathieu, Michael Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet
Riemannian Score-Based Generative Modelling. NeurIPS (2022)
Francisco J. R. Ruiz, Michalis K. Titsias, A. Taylan Cemgil, Arnaud Doucet
Unbiased gradient estimation for variational auto-encoders using coupled Markov chains. UAI (2021)
Michael Arbel, Alexander G. de G. Matthews, Arnaud Doucet
Annealed Flow Transport Monte Carlo. ICML (2021)
Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet
On Instrumental Variable Regression for Deep Offline Policy Evaluation. CoRR (2021)
Philippe Gagnon, Arnaud Doucet
Nonreversible Jump Algorithms for Bayesian Nested Model Selection. J. Comput. Graph. Stat. 30 (2) (2021)
Valentin De Bortoli, Arnaud Doucet, Jeremy Heng, James Thornton
Simulating Diffusion Bridges with Score Matching. CoRR (2021)
Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh
Robust Pruning at Initialization. ICLR (2021)
Vladislav Z. B. Tadic, Arnaud Doucet
Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation. IEEE Trans. Inf. Theory 67 (3) (2021)
Eugenio Clerico, George Deligiannidis, Arnaud Doucet
Conditional Gaussian PAC-Bayes. CoRR (2021)
Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov
Monte Carlo Variational Auto-Encoders. CoRR (2021)
Anthony L. Caterini, Robert Cornish, Dino Sejdinovic, Arnaud Doucet
Variational inference with continuously-indexed normalizing flows. UAI (2021)
Adrien Corenflos, James Thornton, Arnaud Doucet, George Deligiannidis
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport. CoRR (2021)
Emilien Dupont, Yee Whye Teh, Arnaud Doucet
Generative Models as Distributions of Functions. CoRR (2021)
Eugenio Clerico, George Deligiannidis, Arnaud Doucet
Wide stochastic networks: Gaussian limit and PAC-Bayesian training. CoRR (2021)
Andrew Campbell, Yuyang Shi, Thomas Rainforth, Arnaud Doucet
Online Variational Filtering and Parameter Learning. NeurIPS (2021)
Emilien Dupont, Adam Golinski, Milad Alizadeh, Yee Whye Teh, Arnaud Doucet
COIN: COmpression with Implicit Neural representations. CoRR (2021)
Adrien Corenflos, James Thornton, George Deligiannidis, Arnaud Doucet
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport. ICML (2021)
Chris J. Maddison, Daniel Paulin, Yee Whye Teh, Arnaud Doucet
Dual Space Preconditioning for Gradient Descent. SIAM J. Optim. 31 (1) (2021)
David Stutz, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet
Learning Optimal Conformal Classifiers. CoRR (2021)
Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton
Learning Deep Features in Instrumental Variable Regression. ICLR (2021)
Soufiane Hayou, Arnaud Doucet, Judith Rousseau
The Curse of Depth in Kernel Regime. ICBINB@NeurIPS (2021)
Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov
Monte Carlo Variational Auto-Encoders. ICML (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Arnaud Doucet