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Valentin De Bortoli
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Valentin De Bortoli19 visible / 19 total nodes / 55 links

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Related contextCo-authorshipWorks onCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipWorks onWorks onAuthorshipAuthorshipAuthorshipAuthorshipWorks onWorks onWorks onWorks onWorks onWorks onWorks onWorks onWorks onAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalAuthorshipAuthorshipAuthorshipValentin De BortoliAValentin De BortoliResearcherOn the Wasserstein Gradient Flow Interpretation of Drifting ModelsWOn the Wasserstein Grad...preprint / 2026Arthur GrettonAArthur GrettonResearcherLi Kevin WenliangALi Kevin WenliangResearcherAlexandre GalashovAAlexandre GalashovResearcherJames ThorntonAJames ThorntonResearcherArnaud DoucetAArnaud DoucetResearcherMaximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach. Part II: Theoretical AnalysisWMaximum likelihood esti...preprint / 2020Quantitative Propagation of Chaos for SGD in Wide Neural NetworksWQuantitative Propagatio...preprint / 2020Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Application to maximum marginal likelihood and empirical Bayesian estimationWEfficient stochastic op...preprint / 2020Convergence of diffusions and their discretizations: from continuous to discrete processes and backWConvergence of diffusio...preprint / 2020Machine LearningTMachine Learning49008 worksArtificial IntelligenceTArtificial Intelligence22915 worksConditional Simulation Using Diffusion Schrödinger BridgesWConditional Simulation ...preprint / 2022Convergence rates and approximation results for SGD and its continuous-time counterpartWConvergence rates and a...preprint / 2021Maximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach. Part I: Methodology and ExperimentsWMaximum likelihood esti...preprint / 2020Approximate Bayesian Computation with the Sliced-Wasserstein DistanceWApproximate Bayesian Co...preprint / 2020Wavelet Score-Based Generative ModelingWWavelet Score-Based Gen...preprint / 2022Riemannian Diffusion Schrödinger BridgeWRiemannian Diffusion Sc...preprint / 2022
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Valentin De Bortoli

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PaperOn the Wasserstein Gradient Flow Interpretation of Drifting ModelsAuthorship / preprint / 2026PersonArthur GrettonCo-authorship / ResearcherPersonLi Kevin WenliangCo-authorship / ResearcherPersonAlexandre GalashovCo-authorship / ResearcherPersonJames ThorntonCo-authorship / ResearcherPersonArnaud DoucetCo-authorship / ResearcherPaperMaximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach. Part II: Theoretical AnalysisAuthorship / preprint / 2020PaperQuantitative Propagation of Chaos for SGD in Wide Neural NetworksAuthorship / preprint / 2020

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