De Bortoli, Valentin

34 publications

ICML 2025 Accelerated Diffusion Models via Speculative Sampling Valentin De Bortoli, Alexandre Galashov, Arthur Gretton, Arnaud Doucet

ICLR 2025 Deep MMD Gradient Flow Without Adversarial Training Alexandre Galashov, Valentin De Bortoli, Arthur Gretton

AISTATS 2025 Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortoli, Dongxia Wu, Haorui Wang, Aaron M Ferber, Yian Ma, Carla P Gomes, Chao Zhang

ICML 2025 Distributional Diffusion Models with Scoring Rules Valentin De Bortoli, Alexandre Galashov, J Swaroop Guntupalli, Guangyao Zhou, Kevin Patrick Murphy, Arthur Gretton, Arnaud Doucet

NeurIPS 2025 From Stability of Langevin Diffusion to Convergence of Proximal MCMC for Non-Log-Concave Sampling Marien Renaud, Valentin De Bortoli, Arthur Leclaire, Nicolas Papadakis

AISTATS 2025 Implicit Diffusion: Efficient Optimization Through Stochastic Sampling Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet

NeurIPS 2025 On the Edge of Memorization in Diffusion Models Sam Buchanan, Druv Pai, Yi Ma, Valentin De Bortoli

NeurIPS 2025 Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities Tara Akhound-Sadegh, Jungyoon Lee, Joey Bose, Valentin De Bortoli, Arnaud Doucet, Michael M. Bronstein, Dominique Beaini, Siamak Ravanbakhsh, Kirill Neklyudov, Alexander Tong

ICMLW 2024 Implicit Diffusion: Efficient Optimization Through Stochastic Sampling Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet

ICLR 2024 Nearly $d$-Linear Convergence Bounds for Diffusion Models via Stochastic Localization Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis

ICML 2024 Particle Denoising Diffusion Sampler Angus Phillips, Hai-Dang Dau, Michael John Hutchinson, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet

ICLR 2024 Particle Guidance: Non-I.I.D. Diverse Sampling with Diffusion Models Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola

ICLR 2024 Plug-and-Play Posterior Sampling Under Mismatched Measurement and Prior Models Marien Renaud, Jiaming Liu, Valentin De Bortoli, Andres Almansa, Ulugbek Kamilov

NeurIPS 2024 Schrodinger Bridge Flow for Unpaired Data Translation Valentin De Bortoli, Iryna Korshunova, Andriy Mnih, Arnaud Doucet

TMLR 2023 Diffusion Models for Constrained Domains Nic Fishman, Leo Klarner, Valentin De Bortoli, Emile Mathieu, Michael John Hutchinson

NeurIPS 2023 Diffusion Schrödinger Bridge Matching Yuyang Shi, Valentin De Bortoli, Andrew Campbell, Arnaud Doucet

NeurIPS 2023 Geometric Neural Diffusion Processes Emile Mathieu, Vincent Dutordoir, Michael Hutchinson, Valentin De Bortoli, Yee Whye Teh, Richard Turner

NeurIPS 2023 Metropolis Sampling for Constrained Diffusion Models Nic Fishman, Leo Klarner, Emile Mathieu, Michael Hutchinson, Valentin De Bortoli

NeurIPSW 2023 Particle Guidance: Non-I.I.D. Diverse Sampling with Diffusion Models Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi Jaakkola

ICML 2023 SE(3) Diffusion Model with Application to Protein Backbone Generation Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi Jaakkola

NeurIPS 2023 Trans-Dimensional Generative Modeling via Jump Diffusion Models Andrew Campbell, William Harvey, Christian Weilbach, Valentin De Bortoli, Thomas Rainforth, Arnaud Doucet

NeurIPS 2023 Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters Maxence Noble, Valentin De Bortoli, Arnaud Doucet, Alain Durmus

ICMLW 2023 Unbalanced Diffusion Schrödinger Bridge Matteo Pariset, Ya-Ping Hsieh, Charlotte Bunne, Andreas Krause, Valentin De Bortoli

NeurIPS 2023 Unbiased Constrained Sampling with Self-Concordant Barrier Hamiltonian Monte Carlo Maxence Noble, Valentin De Bortoli, Alain Durmus

NeurIPS 2022 A Continuous Time Framework for Discrete Denoising Models Andrew Campbell, Joe Benton, Valentin De Bortoli, Thomas Rainforth, George Deligiannidis, Arnaud Doucet

NeurIPS 2022 Can Push-Forward Generative Models Fit Multimodal Distributions? Antoine Salmona, Valentin De Bortoli, Julie Delon, Agnes Desolneux

UAI 2022 Conditional Simulation Using Diffusion Schrödinger Bridges Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet

TMLR 2022 Convergence of Denoising Diffusion Models Under the Manifold Hypothesis Valentin De Bortoli

NeurIPS 2022 Riemannian Score-Based Generative Modelling Valentin De Bortoli, Emile Mathieu, Michael Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet

NeurIPSW 2022 Spectral Diffusion Processes Angus Phillips, Thomas Seror, Michael John Hutchinson, Valentin De Bortoli, Arnaud Doucet, Emile Mathieu

NeurIPS 2022 Wavelet Score-Based Generative Modeling Florentin Guth, Simon Coste, Valentin De Bortoli, Stephane Mallat

COLT 2021 Convergence Rates and Approximation Results for SGD and Its Continuous-Time Counterpart Xavier Fontaine, Valentin De Bortoli, Alain Durmus

NeurIPS 2021 Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet

NeurIPS 2020 Quantitative Propagation of Chaos for SGD in Wide Neural Networks Valentin De Bortoli, Alain Durmus, Xavier Fontaine, Umut Simsekli