Valentin De Bortoli

90 papers A* 22A 3Misc 1Journal 62Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Count Bridges enable Modeling and Deconvolving Transcriptomic Data. CoRR Nic Fishman, Gokul Gowri, Tanush Kumar, Jiaqi Lu, Valentin De Bortoli, Jonathan Gootenberg, Omar Abudayyeh
2026	J	`jnl`	Dimension-free error estimate for diffusion model and optimal scheduling. Trans. Mach. Learn. Res. Valentin De Bortoli, Romuald Elie, Anna Kazeykina, Zhenjie Ren, Jiacheng Zhang
2026	J	`jnl`	Seasoning Generative Models for a Generalization Aftertaste. CoRR Hisham Husain, Valentin De Bortoli, Richard Nock
2025	A*	`conf`	Accelerated Diffusion Models via Speculative Sampling. ICML Valentin De Bortoli, Alexandre Galashov, Arthur Gretton, Arnaud Doucet
2025	J	`jnl`	Accelerated Diffusion Models via Speculative Sampling. CoRR Valentin De Bortoli, Alexandre Galashov, Arthur Gretton, Arnaud Doucet
2025	A*	`conf`	Deep MMD Gradient Flow without adversarial training. ICLR Alexandre Galashov, Valentin De Bortoli, Arthur Gretton
2025	A	`conf`	Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints. AISTATS 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
2025	J	`jnl`	Dimension-free error estimate for diffusion model and optimal scheduling. CoRR Valentin De Bortoli, Romuald Elie, Anna Kazeykina, Zhenjie Ren, Jiacheng Zhang
2025	A*	`conf`	Distributional Diffusion Models with Scoring Rules. ICML Valentin De Bortoli, Alexandre Galashov, J. Swaroop Guntupalli, Guangyao Zhou, Kevin Patrick Murphy, Arthur Gretton, Arnaud Doucet
2025	J	`jnl`	Distributional Diffusion Models with Scoring Rules. CoRR Valentin De Bortoli, Alexandre Galashov, J. Swaroop Guntupalli, Guangyao Zhou, Kevin Murphy, Arthur Gretton, Arnaud Doucet
2025	J	`jnl`	From stability of Langevin diffusion to convergence of proximal MCMC for non-log-concave sampling. CoRR Marien Renaud, Valentin De Bortoli, Arthur Leclaire, Nicolas Papadakis
2025	A	`conf`	Implicit Diffusion: Efficient optimization through stochastic sampling. AISTATS Pierre Marion, Anna Korba, Peter L. Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet
2025	J	`jnl`	Learn to Guide Your Diffusion Model. CoRR Alexandre Galashov, Ashwini Pokle, Arnaud Doucet, Arthur Gretton, Mauricio Delbracio, Valentin De Bortoli
2025	J	`jnl`	On the Edge of Memorization in Diffusion Models. CoRR Sam Buchanan, Druv Pai, Yi Ma, Valentin De Bortoli
2025	J	`jnl`	Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities. CoRR Tara Akhound-Sadegh, Jungyoon Lee, Avishek Joey Bose, Valentin De Bortoli, Arnaud Doucet, Michael M. Bronstein, Dominique Beaini, Siamak Ravanbakhsh, Kirill Neklyudov, Alexander Tong
2025	J	`jnl`	Self-Speculative Masked Diffusions. CoRR Andrew Campbell, Valentin De Bortoli, Jiaxin Shi, Arnaud Doucet
2024	J	`jnl`	Deep MMD Gradient Flow without adversarial training. CoRR Alexandre Galashov, Valentin De Bortoli, Arthur Gretton
2024	J	`jnl`	Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints. CoRR Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortoli, Haorui Wang, Dongxia Wu, Aaron M. Ferber, Yi-An Ma, Carla P. Gomes, Chao Zhang
2024	J	`jnl`	Dynamical Regimes of Diffusion Models. CoRR Giulio Biroli, Tony Bonnaire, Valentin De Bortoli, Marc Mézard
2024	J	`jnl`	Implicit Diffusion: Efficient Optimization through Stochastic Sampling. CoRR Pierre Marion, Anna Korba, Peter L. Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet
2024	A*	`conf`	Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization. ICLR Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis
2024	A*	`conf`	Particle Denoising Diffusion Sampler. ICML Angus Phillips, Hai-Dang Dau, Michael John Hutchinson, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
2024	J	`jnl`	Particle Denoising Diffusion Sampler. CoRR Angus Phillips, Hai-Dang Dau, Michael John Hutchinson, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
2024	A*	`conf`	Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models. ICLR Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola
2024	A*	`conf`	Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models. ICLR Marien Renaud, Jiaming Liu, Valentin De Bortoli, Andrés Almansa, Ulugbek Kamilov
2024	J	`jnl`	Review of wavelet-based unsupervised texture segmentation, advantage of adaptive wavelets. CoRR Yuan Huang, Valentin De Bortoli, Fugen Zhou, Jérôme Gilles
2024	A*	`conf`	Schrodinger Bridge Flow for Unpaired Data Translation. NeurIPS Valentin De Bortoli, Iryna Korshunova, Andriy Mnih, Arnaud Doucet
2024	J	`jnl`	Schrödinger Bridge Flow for Unpaired Data Translation. CoRR Valentin De Bortoli, Iryna Korshunova, Andriy Mnih, Arnaud Doucet
2024	J	`jnl`	Target Score Matching. CoRR Valentin De Bortoli, Michael J. Hutchinson, Peter Wirnsberger, Arnaud Doucet
2023	J	`jnl`	Augmented Bridge Matching. CoRR Valentin De Bortoli, Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou, Weilie Nie
2023	J	`jnl`	Diffusion Models for Constrained Domains. CoRR Nic Fishman, Leo Klarner, Valentin De Bortoli, Emile Mathieu, Michael J. Hutchinson
2023	J	`jnl`	Diffusion Models for Constrained Domains. Trans. Mach. Learn. Res. Nic Fishman, Leo Klarner, Valentin De Bortoli, Emile Mathieu, Michael John Hutchinson
2023	A*	`conf`	Diffusion Schrödinger Bridge Matching. NeurIPS Yuyang Shi, Valentin De Bortoli, Andrew Campbell, Arnaud Doucet
2023	J	`jnl`	Diffusion Schrödinger Bridge Matching. CoRR Yuyang Shi, Valentin De Bortoli, Andrew Campbell, Arnaud Doucet
2023	A*	`conf`	Geometric Neural Diffusion Processes. NeurIPS Emile Mathieu, Vincent Dutordoir, Michael J. Hutchinson, Valentin De Bortoli, Yee Whye Teh, Richard E. Turner
2023	J	`jnl`	Geometric Neural Diffusion Processes. CoRR Emile Mathieu, Vincent Dutordoir, Michael J. Hutchinson, Valentin De Bortoli, Yee Whye Teh, Richard E. Turner
2023	J	`jnl`	Linear Convergence Bounds for Diffusion Models via Stochastic Localization. CoRR Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis
2023	A*	`conf`	Metropolis Sampling for Constrained Diffusion Models. NeurIPS Nic Fishman, Leo Klarner, Emile Mathieu, Michael J. Hutchinson, Valentin De Bortoli
2023	J	`jnl`	Metropolis Sampling for Constrained Diffusion Models. CoRR Nic Fishman, Leo Klarner, Emile Mathieu, Michael J. Hutchinson, Valentin De Bortoli
2023	J	`jnl`	On Maximum a Posteriori Estimation with Plug & Play Priors and Stochastic Gradient Descent. J. Math. Imaging Vis. Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
2023	J	`jnl`	Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models. CoRR Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola
2023	J	`jnl`	Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models. CoRR Marien Renaud, Jiaming Liu, Valentin De Bortoli, Andrés Almansa, Ulugbek S. Kamilov
2023	A*	`conf`	SE(3) diffusion model with application to protein backbone generation. ICML Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola
2023	J	`jnl`	SE(3) diffusion model with application to protein backbone generation. CoRR Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola
2023	A*	`conf`	Trans-Dimensional Generative Modeling via Jump Diffusion Models. NeurIPS Andrew Campbell, William Harvey, Christian Weilbach, Valentin De Bortoli, Thomas Rainforth, Arnaud Doucet
2023	J	`jnl`	Trans-Dimensional Generative Modeling via Jump Diffusion Models. CoRR Andrew Campbell, William Harvey, Christian Weilbach, Valentin De Bortoli, Tom Rainforth, Arnaud Doucet
2023	A*	`conf`	Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters. NeurIPS Maxence Noble, Valentin De Bortoli, Arnaud Doucet, Alain Durmus
2023	J	`jnl`	Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters. CoRR Maxence Noble, Valentin De Bortoli, Arnaud Doucet, Alain Durmus
2023	J	`jnl`	Unbalanced Diffusion Schrödinger Bridge. CoRR Matteo Pariset, Ya-Ping Hsieh, Charlotte Bunne, Andreas Krause, Valentin De Bortoli
2023	A*	`conf`	Unbiased constrained sampling with Self-Concordant Barrier Hamiltonian Monte Carlo. NeurIPS Maxence Noble, Valentin De Bortoli, Alain Durmus
2022	A*	`conf`	A Continuous Time Framework for Discrete Denoising Models. NeurIPS Andrew Campbell, Joe Benton, Valentin De Bortoli, Thomas Rainforth, George Deligiannidis, Arnaud Doucet
2022	J	`jnl`	A Continuous Time Framework for Discrete Denoising Models. CoRR Andrew Campbell, Joe Benton, Valentin De Bortoli, Tom Rainforth, George Deligiannidis, Arnaud Doucet
2022	J	`jnl`	Barrier Hamiltonian Monte Carlo. CoRR Maxence Noble, Valentin De Bortoli, Alain Durmus
2022	J	`jnl`	Bayesian Imaging Using Plug & Play Priors: When Langevin Meets Tweedie. SIAM J. Imaging Sci. Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
2022	A*	`conf`	Can Push-forward Generative Models Fit Multimodal Distributions? NeurIPS Antoine Salmona, Valentin De Bortoli, Julie Delon, Agnès Desolneux
2022	J	`jnl`	Can Push-forward Generative Models Fit Multimodal Distributions? CoRR Antoine Salmona, Valentin De Bortoli, Julie Delon, Agnès Desolneux
2022	J	`jnl`	Conditional Simulation Using Diffusion Schrödinger Bridges. CoRR Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
2022	A	`conf`	Conditional simulation using diffusion Schrödinger bridges. UAI Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
2022	J	`jnl`	Convergence of denoising diffusion models under the manifold hypothesis. CoRR Valentin De Bortoli
2022	J	`jnl`	Convergence of denoising diffusion models under the manifold hypothesis. Trans. Mach. Learn. Res. Valentin De Bortoli
2022	J	`jnl`	From Denoising Diffusions to Denoising Markov Models. CoRR Joe Benton, Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
2022	J	`jnl`	On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent. CoRR Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
2022	J	`jnl`	Riemannian Diffusion Schrödinger Bridge. CoRR James Thornton, Michael J. Hutchinson, Emile Mathieu, Valentin De Bortoli, Yee Whye Teh, Arnaud Doucet
2022	J	`jnl`	Riemannian Score-Based Generative Modeling. CoRR Valentin De Bortoli, Emile Mathieu, Michael J. Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet
2022	A*	`conf`	Riemannian Score-Based Generative Modelling. NeurIPS Valentin De Bortoli, Emile Mathieu, Michael J. Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet
2022	J	`jnl`	Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows. CoRR Francesca R. Crucinio, Valentin De Bortoli, Arnaud Doucet, Adam M. Johansen
2022	J	`jnl`	Spectral Diffusion Processes. CoRR Angus Phillips, Thomas Seror, Michael J. Hutchinson, Valentin De Bortoli, Arnaud Doucet, Emile Mathieu
2022	A*	`conf`	Wavelet Score-Based Generative Modeling. NeurIPS Florentin Guth, Simon Coste, Valentin De Bortoli, Stéphane Mallat
2022	J	`jnl`	Wavelet Score-Based Generative Modeling. CoRR Florentin Guth, Simon Coste, Valentin De Bortoli, Stéphane Mallat
2021	J	`jnl`	Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie. CoRR Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
2021	A*	`conf`	Convergence rates and approximation results for SGD and its continuous-time counterpart. COLT Xavier Fontaine, Valentin De Bortoli, Alain Durmus
2021	A*	`conf`	Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling. NeurIPS Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet
2021	J	`jnl`	Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling. CoRR Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet
2021	J	`jnl`	Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Stat. Comput. Valentin De Bortoli, Alain Durmus, Marcelo Pereyra, Ana Fernandez Vidal
2021	J	`jnl`	Maximum Entropy Methods for Texture Synthesis: Theory and Practice. SIAM J. Math. Data Sci. Valentin De Bortoli, Agnès Desolneux, Alain Durmus, Bruno Galerne, Arthur Leclaire
2021	J	`jnl`	On quantitative Laplace-type convergence results for some exponential probability measures, with two applications. CoRR Valentin De Bortoli, Agnès Desolneux
2021	J	`jnl`	Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure. CoRR George Deligiannidis, Valentin De Bortoli, Arnaud Doucet
2021	J	`jnl`	Simulating Diffusion Bridges with Score Matching. CoRR Valentin De Bortoli, Arnaud Doucet, Jeremy Heng, James Thornton
2020	Misc	`conf`	Approximate Bayesian Computation with the Sliced-Wasserstein Distance. ICASSP Kimia Nadjahi, Valentin De Bortoli, Alain Durmus, Roland Badeau, Umut Simsekli
2020	J	`jnl`	Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach Part I: Methodology and Experiments. SIAM J. Imaging Sci. Ana Fernandez Vidal, Valentin De Bortoli, Marcelo Pereyra, Alain Durmus
2020	J	`jnl`	Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach. Part II: Theoretical Analysis. SIAM J. Imaging Sci. Valentin De Bortoli, Alain Durmus, Marcelo Pereyra, Ana Fernandez Vidal
2020	A*	`conf`	Quantitative Propagation of Chaos for SGD in Wide Neural Networks. NeurIPS Valentin De Bortoli, Alain Durmus, Xavier Fontaine, Umut Simsekli
2020	J	`jnl`	Quantitative Propagation of Chaos for SGD in Wide Neural Networks. CoRR Valentin De Bortoli, Alain Durmus, Xavier Fontaine, Umut Simsekli
2020	—	`—`	Statistiques non locales dans les images: modélisation, estimation et échantillonnage. (Non-local statistics in images: modelisation, estimation and sampling). Valentin De Bortoli
2019	—	`conf`	Macrocanonical Models for Texture Synthesis. SSVM Valentin De Bortoli, Agnès Desolneux, Bruno Galerne, Arthur Leclaire
2019	J	`jnl`	Macrocanonical Models for Texture Synthesis. CoRR Valentin De Bortoli, Agnès Desolneux, Bruno Galerne, Arthur Leclaire
2019	J	`jnl`	Maximum entropy methods for texture synthesis: theory and practice. CoRR Valentin De Bortoli, Agnès Desolneux, Alain Durmus, Bruno Galerne, Arthur Leclaire
2019	J	`jnl`	Patch Redundancy in Images: A Statistical Testing Framework and Some Applications. SIAM J. Imaging Sci. Valentin De Bortoli, Agnès Desolneux, Bruno Galerne, Arthur Leclaire
2019	J	`jnl`	Patch redundancy in images: a statistical testing framework and some applications. CoRR Valentin De Bortoli, Agnès Desolneux, Bruno Galerne, Arthur Leclaire
2018	J	`jnl`	Review of wavelet-based unsupervised texture segmentation, advantage of adaptive wavelets. IET Image Process. Yuan Huang, Valentin De Bortoli, Fugen Zhou, Jérôme Gilles