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Alain Durmus

  1. Non-asymptotic convergence analysis for the Unadjusted Langevin Algorithm
    2015/07/17 by Alain Durmus, Durmus, Alain, Éric Moulines +1 · 30 citations
    Decision Sciences · Mathematics · #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Markov Chains and Monte Carlo Methods #Methodology (stat.ME) #Probability and Risk Models #Random Matrices and Applications #Statistics Theory (math.ST)
  2. High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm
    2016/05/05 by Alain Durmus, Durmus, Alain, Éric Moulines +1 · 18 citations
    Mathematics · Physics and Astronomy · #Markov Chains and Monte Carlo Methods #Statistical Methods and Inference #Statistical Mechanics and Entropy
  3. Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains
    2017/07/20 by Aymeric Dieuleveut, Dieuleveut, Aymeric, Alain Durmus +3 · 18 citations
    Computer Science · Mathematics · Physics and Astronomy · #Stochastic Gradient Optimization Techniques #Markov Chains and Monte Carlo Methods #stochastic dynamics and bifurcation
  4. Efficient Bayesian computation by proximal Markov chain Monte Carlo: when Langevin meets Moreau
    2016/12/22 by Alain Durmus, Durmus, Alain, Éric Moulines +3 · 14 citations
    Medicine · Engineering · Mathematics · #Medical Imaging Techniques and Applications #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference
  5. Bridging the gap between constant step size stochastic gradient descent and Markov chains
    2020/06/01 by Aymeric Dieuleveut, Alain Durmus, Francis Bach · 12 citations
  6. Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
    2018/06/21 by Antoine Liutkus, Umut Ş Imşekli, Liutkus, Antoine +8 · 18 citations
    Computer Science · Mathematics · #Generative Adversarial Networks and Image Synthesis #Stochastic Gradient Optimization Techniques #Markov Chains and Monte Carlo Methods
  7. The promises and pitfalls of Stochastic Gradient Langevin Dynamics
    2018/11/25 by Nicolas Brosse, Alain Durmus, Brosse, Nicolas +3 · 9 citations
    Computer Science · Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Quantum Computing Algorithms and Architecture #Quantum many-body systems
  8. Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo
    2017/05/24 by Nicolas Brosse, Brosse, Nicolas, Alain Durmus +5 · 8 citations
    Mathematics · #Markov Chains and Monte Carlo Methods #Statistical Methods and Bayesian Inference #Statistical Methods and Inference
  9. The Tamed Unadjusted Langevin Algorithm
    2017/10/16 by Nicolas Brosse, Alain Durmus, Brosse, Nicolas +5 · 6 citations
    #FOS: Computer and information sciences #Methodology (stat.ME)
  10. KL Convergence Guarantees for Score diffusion models under minimal data assumptions
    2023/08/23 by Giovanni Conforti, Conforti, Giovanni, Alain Durmus +3 · 10 citations
    Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Statistical Mechanics and Entropy #Statistical Methods and Bayesian Inference #Statistics Theory (math.ST)
  11. Watermarking Makes Language Models Radioactive
    2024/02/22 by Tom Sander, Sander, Tom, Pierre Fernandez +7 · 10 citations
    Computer Science · #Natural Language Processing Techniques #Topic Modeling #Speech Recognition and Synthesis
  12. FedPop: A Bayesian Approach for Personalised Federated Learning
    2022/06/07 by Nikita Kotelevskii, Maxime Vono, Kotelevskii, Nikita +4 · 6 citations
    Computer Science · #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Privacy-Preserving Technologies in Data #Recommender Systems and Techniques
  13. Fast Approximation of the Sliced-Wasserstein Distance Using\n Concentration of Random Projections
    2021/06/29 by Kimia Nadjahi, Nadjahi, Kimia, Alain Durmus +7 · 5 citations
    Mathematics · #Geometric Analysis and Curvature Flows
  14. Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize
    2021/06/02 by Alain Durmus, Éric Moulines, Durmus, Alain +9 · 6 citations
    Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Probability (math.PR) #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST) #Stochastic Gradient Optimization Techniques
  15. Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation
    2022/07/10 by Alain Durmus, Éric Moulines, Durmus, Alain +5 · 6 citations
    Engineering · Mathematics · #60J20 #62L20 #Control Systems and Identification #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Probability (math.PR) #Statistical Methods and Inference #Statistics Theory (math.ST)
  16. Forward Event-Chain Monte Carlo: Fast sampling by randomness control in irreversible Markov chains
    2017/02/27 by Manon Michel, Michel, Manon, Alain Durmus +3 · 3 citations
    Mathematics · Physics and Astronomy · #Computation (stat.CO) #FOS: Computer and information sciences #Markov Chains and Monte Carlo Methods #Theoretical and Computational Physics
  17. Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Application to maximum marginal likelihood and empirical Bayesian estimation
    2019/06/28 by Valentin De Bortoli, De Bortoli, Valentin, Alain Durmus +5 · 4 citations
    Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Blind Source Separation Techniques #Computation (stat.CO) #FOS: Computer and information sciences #Markov Chains and Monte Carlo Methods
  18. On the convergence of Hamiltonian Monte Carlo
    2017/04/29 by Alain Durmus, Durmus, Alain, Éric Moulines +3 · 5 citations
    Mathematics · #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Markov Chains and Monte Carlo Methods #Mathematical Approximation and Integration #Probability (math.PR) #Stochastic processes and statistical mechanics
  19. Variational Diffusion Posterior Sampling with Midpoint Guidance
    2024/10/13 by Badr Moufad, Yazid Janati, Moufad, Badr +11 · 10 citations
    Engineering · #FOS: Computer and information sciences #Image Processing Techniques and Applications #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Ultrasonics and Acoustic Wave Propagation
  20. On Sampling with Approximate Transport Maps
    2023/02/09 by Louis Grenioux, Alain Durmus, Grenioux, Louis +5 · 4 citations
    Mathematics · Computer Science · Medicine · #Markov Chains and Monte Carlo Methods #Generative Adversarial Networks and Image Synthesis #Advanced Neuroimaging Techniques and Applications
  21. Stochastic Localization via Iterative Posterior Sampling
    2024/02/16 by Louis Grenioux, Grenioux, Louis, Maxence Noble +5 · 4 citations
    Computer Science · #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Target Tracking and Data Fusion in Sensor Networks
  22. VITS : Variational Inference Thompson Sampling for contextual bandits
    2023/07/19 by Pierre Clavier, Tom Huix, Clavier, Pierre +3 · 3 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mobile Crowdsensing and Crowdsourcing
  23. Discrete sticky couplings of functional autoregressive processes
    2021/04/14 by Alain Durmus, Durmus, Alain, Andreas Eberle +7 · 2 citations
    Mathematics · #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Point processes and geometric inequalities #Probability (math.PR) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference
  24. Monte Carlo Variational Auto-Encoders
    2021/06/30 by Achille Thin, Nikita Kotelevskii, Thin, Achille +9 · 2 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Speech Recognition and Synthesis
  25. Local-Global MCMC kernels: the best of both worlds
    2021/11/04 by Sergey Samsonov, Samsonov, Sergey, Evgeny Lagutin +9 · 2 citations
    Computer Science · Mathematics · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods
  26. The exponential turnpike phenomenon for mean field game systems: weakly monotone drifts and small interactions
    2024/09/13 by Alekos Cecchin, Giovanni Conforti, Cecchin, Alekos +5 · 4 citations
    Economics, Econometrics and Finance · Mathematics · Physics and Astronomy · #35B40 #49N80 #60H30 #60J60 #93E20 #Analysis of PDEs (math.AP) #FOS: Mathematics #Optimization and Control (math.OC) #Probability (math.PR) #Quantum chaos and dynamical systems #Stochastic processes and financial applications #Stochastic processes and statistical mechanics
  27. Incentivized Learning in Principal-Agent Bandit Games
    2024/03/06 by Antoine Scheid, Scheid, Antoine, Daniil Tiapkin +12 · 3 citations
    Decision Sciences · Social Sciences · #Advanced Bandit Algorithms Research #Auction Theory and Applications #Experimental Behavioral Economics Studies
  28. A Mixture-Based Framework for Guiding Diffusion Models
    2025/02/05 by Yazid Janati, Janati, Yazid, Badr Moufad +9 · 7 citations
    Computer Science · #Bayesian Methods and Mixture Models
  29. Normalizing constants of log-concave densities
    2017/07/03 by Nicolas Brosse, Brosse, Nicolas, Alain Durmus +3 · 1 citation
    Computer Science · Mathematics · #60F25 #60J05 #62L10 (Primary) 65C40 #65C05 #74G10 #74G15 (Secondary) #FOS: Computer and information sciences #Markov Chains and Monte Carlo Methods #Methodology (stat.ME) #Statistical Methods and Inference #Stochastic Gradient Optimization Techniques
  30. Theoretical guarantees in KL for Diffusion Flow Matching
    2024/09/12 by Marta Gentiloni Silveri, Silveri, Marta Gentiloni, Giovanni Conforti +3 · 4 citations
    Engineering · #Advanced Control Systems Optimization #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Probability (math.PR)
  31. Probability and moment inequalities for additive functionals of geometrically ergodic Markov chains
    2021/09/01 by Alain Durmus, Éric Moulines, Durmus, Alain +5 · 2 citations
    Mathematics · #60E15 #60J20 #65C40 #FOS: Mathematics #Geometric Analysis and Curvature Flows #Markov Chains and Monte Carlo Methods #Point processes and geometric inequalities #Probability (math.PR)
  32. Differentially Private Representation Learning via Image Captioning
    2024/03/04 by Tom Sander, Sander, Tom, Yaodong Yu +11 · 2 citations
    Computer Science · Medicine · #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications
  33. Nonreversible MCMC from conditional invertible transforms: a complete\n recipe with convergence guarantees
    2020/12/31 by Achille Thin, Thin, Achille, Christophe Andrieu +10 · 1 citation
    Computer Science · Mathematics · Physics and Astronomy · #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Model Reduction and Neural Networks #NMR spectroscopy and applications #Theoretical and Computational Physics
  34. Quantitative contraction rates for Sinkhorn's algorithm: beyond bounded costs and compact marginals
    2023/04/10 by Giovanni Conforti, Alain Durmus, Conforti, Giovanni +3 · 2 citations
    Mathematics · #47D07 (Secondary) #49Q22 #90C25 (Primary) 49N05 #93E20 #FOS: Mathematics #Geometric Analysis and Curvature Flows #Nonlinear Partial Differential Equations #Numerical methods in inverse problems #Optimization and Control (math.OC) #Probability (math.PR)
  35. On the convergence of dynamic implementations of Hamiltonian Monte Carlo and no U-turn samplers
    2023/07/07 by Alain Durmus, Samuel Gruffaz, Durmus, Alain +7 · 1 voice · 1 citation
    Computer Science · Engineering · Mathematics · #Ferroelectric and Negative Capacitance Devices #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods
  36. Heavy-Tailed Diffusion with Denoising Lévy Probabilistic Models
    2024/07/26 by Dario Shariatian, Shariatian, Dario, Umut Şimşekli +3 · 2 citations
    Computer Science · Decision Sciences · #Advanced Database Systems and Queries #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Simulation Techniques and Applications #Time Series Analysis and Forecasting
  37. Learned Reference-based Diffusion Sampling for multi-modal distributions
    2024/10/25 by Maxence Noble, Noble, Maxence, Louis Grenioux +5 · 2 citations
    Computer Science · #Speech and Audio Processing #Bayesian Methods and Mixture Models #Speech Recognition and Synthesis
  38. Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent
    2023/10/27 by Krunoslav Lehman Pavasovic, Alain Durmus, Pavasovic, Krunoslav Lehman +3 · 1 citation
    Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stochastic Gradient Optimization Techniques
  39. Rosenthal-type inequalities for linear statistics of Markov chains
    2023/03/10 by Alain Durmus, Durmus, Alain, Éric Moulines +7 · 2 citations
    Mathematics · #60E15 #60J20 #65C40 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Point processes and geometric inequalities #Probability (math.PR) #Statistics Theory (math.ST) #Stochastic processes and statistical mechanics
  40. Conditional Diffusion Models with Classifier-Free Gibbs-like Guidance
    2025/05/27 by Badr Moufad, Moufad, Badr, Yazid Janati +9 · 2 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Methodology (stat.ME) #Statistical Mechanics and Entropy #Target Tracking and Data Fusion in Sensor Networks
  41. Twisted Schrödinger Bridge Matching
    2026/07/18 by Maxence Noble, Marie Scheid, Yazid Janati +2
    #stat.ML #cs.LG