Laboratoire de Physique ENS de Lyon - UMR 5672 https://www.ens-lyon.fr/PHYSIQUE i-DEQ: A stable inertial deep equilibrium model for image restoration https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/i-deq-a-stable-inertial-deep-equilibrium-model-for-image-restoration Antonin Clerc (Institut Mathématique de Bordeaux) 2026-09-29T09:01:11Z Event Testing Magnitude Dependence in Earthquake Occurrence: Correlation or Observation Bias? https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Petrillo Giuseppe Petrillo (CNRS, Chaire Prof. Junior ; LP ENSL) 2026-06-22T12:30:14Z Event Learning jump-diffusion dynamics from irregularly sampled data https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/copy_of_mlsp2026_Malgouyres Tim Jahn (TU Berlin) 2026-06-30T09:11:56Z Event Deep Equilibrium models for Poisson Imaging Inverse problems via Mirror Descent https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Daniele Christian Daniele (PhD at Malga, Università degli Studi di Genova) 2026-06-09T07:17:17Z Event Geometry-induced Regularization in Deep ReLU Neural Networks https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Malgouyres François Malgouyres (Institut Mathématiques de Toulouse) 2026-06-11T07:18:59Z Event Neural and Tensor Networks for PDEs: PINNs, Neural Operators, and Low-Rank Approximation https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Marcati Carlo Marcati (Chaire Prof. Junior, ICJ, Lyon 1) 2026-04-20T08:23:39Z Event Expressivity bottlenecks in neural networks within the framework of neural architecture search. https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Verbockhaven Manon Verbockhaven (post-doc équipe Ockham, LIP, Inria, ENSL) 2026-04-20T08:19:13Z Event The Long-Run Behavior of SGD in Non-Convex Landscapes: A Large Deviation Analysis https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_%20Azizian Waïss Azizian (PhD student in machine learning and optimization in LJK, UGA, Grenoble) 2026-04-01T08:01:13Z Event Multilevel Preconditioning Strategies for Convex Optimization Methods in Image Deblurring https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Binda Claudia Binda (post-doc Univeristà dell'Insubria, Como, Italie) 2026-02-26T07:38:44Z Event Regularity of the score and convergence rates of generative diffusion models https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Stephanovitch Arthur Stéphanovitch (postdoctoral researcher at ENSAE-CREST) 2026-02-23T07:49:59Z Event Expressivity of lazy sinusoidal neural networks: a frame-theoretic approach https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Mil-homens-Cavaco Nicolas Mil-homens Cavaco (PhD candidate, UCLouvain) 2026-02-26T07:40:25Z Event TBA https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Neumayer Sebastian Neumayer (Professor, TU Chemnitz) 2026-02-23T07:41:23Z Event Random Wavelet Features for Graph Kernel Machines https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_de_Bassompierre Valentin de Bassompierre (PhD candidate, UCLouvain) 2026-02-23T07:33:01Z Event The strange case of the binary perceptron: when standard statistical mechanics fails https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Barbier Damien Barbier (post-doc, Department of Computer Sciences (Bocconi University), Milan, Italy) 2026-01-25T14:10:11Z Event Implicit Bias in Gradient Flow Learning: Results, Open Questions, and Emerging Dynamics https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Pillaud-Vivien Loucas Pillaud-Vivien (assistant professor at Ecole des Ponts ParisTech, CERMICS) 2026-01-25T14:09:44Z Event Kernelization of Natural Gradient Methods for Physics Informed Machine-Learning https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2026_Schwencke Nilo Schwencke (PhD @ Paris-Saclay University) 2026-01-14T09:26:32Z Event Rank-one projections for compressive radio interferometric imaging https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_L_Jacques Laurent Jacques (Professor and FNRS Senior Research Associate, ICTEAM institute at UCLouvain, Belgium ; invited Professor at Collegium Lyon, 2025-2026) 2026-01-07T12:49:34Z Event What is a good matching of probability measures ? A counterfactual lens on transport maps https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Ganassali Luca Ganassali (Department of Mathematics, Université Paris-Saclay ; Inria team Celeste) 2025-12-02T10:36:24Z Event Bounded Random Features for Grassmannian Kernels with Rank-One Projections https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_delogne Rémi Delogne (PhD Student, UClouvain) 2025-11-24T08:10:28Z Event Why Diffusion Models Don't Memorize: The Role of Implicit Dynamical Regularization in Training https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_urfin Raphaël Urfin (PhD Student, École Normale Supérieure - PSL) 2025-11-10T09:50:05Z Event Toward Understanding the Generalization of Flow Matching https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_bertrand Quentin Bertrand (Inria, equipe MALICE, Saint-Etienne) 2025-11-10T08:25:32Z Event BeWater : Vers des rassemblements décentralisés efficaces dans les réseaux de rues https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_moinard Guillaume Moinard (doctorant, LIP6, Sorbonne Université) 2025-10-07T11:40:07Z Event Theoretical Guarantees in Inverse Problems: From Self-Supervised Networks to Blind Tikhonov Regularization https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Buskulic Nathan Buskulic (post-doc at Machine Learning center of Genova (MaLGa)) 2025-10-07T11:49:14Z Event Deep Learning Techniques for HDR Modulo Imaging https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/copy_of_mlsp2025_Buskulic Brayan Monroy (Universidad Industrial de Santander, Colombia) 2025-09-15T06:28:26Z Event A fast semi-exact primal-dual method for steady viscoplastic flows https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Bouchut François Bouchut (DR CNRS, Université Gustave Eiffel) 2025-06-12T21:49:50Z Event Survival Models: Proper Scoring Rule and Stochastic Optimization with Competing Risks https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Alberge Julie Alberge (PhD Student, inria Saclay, Soda team) 2025-06-13T09:20:50Z Event Tracking cellular processes in living tissues: from pattern recognition to pattern mining https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Roudot Philippe Roudot (CNRS Researcher and CENTURI Group Leader @ Institut Fresnel, Marseille) 2025-05-26T06:27:19Z Event Variational Diffusion Posterior Sampling with Midpoint Guidance. https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Moufad Badr Moufad (PhD student, Ecole Polytechnique) 2025-03-28T13:55:55Z Event Training a neural network for data reduction and better generalization: towards intelligent artificial intelligence. https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Sardy Sylvain Sardy (Prof. associé, Université de Genève) 2025-04-07T07:01:00Z Event Deep Learning Methods for Sparse-View 3D X-ray Computed Tomography https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Vo Romain Vo (post-doc, Lab. Physique, ENS de Lyon) 2025-04-07T07:01:50Z Event Image decomposition in Fluorescence Microscopy: A posterior sampling based approach https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Ashesh Ashesh Ashesh (PHD Student, Human Technopole, Milano, Italy) 2025-03-18T08:36:58Z Event Node Regression on Latent Position Random Graphs via Local Averaging https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Gjorgjevski Martin Gjorgjevski (PHD Student - GIPSA-lab) 2025-02-24T09:30:04Z Event Properties of Discrete Sliced Wasserstein Losses https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Tanguy Eloi Tanguy (PHD Student, Université Paris Cité) 2025-02-18T11:56:30Z Event An inhomogeneous Poisson process model for text time-series signals https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_Chalkiadakis Ioannis Chalkiadakis (post-doc CNRS, ISC-PIF) 2025-01-27T07:45:09Z Event How Smooth Is Attention? https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_castin Valérie Castin (PhD student, ENS PSL) 2025-01-20T14:55:47Z Event Low-rank and sparse tensor decompositions with applications in signal processing https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/caiafa_mlsp Cesar CAIAFA (CONICET, UBA) 2025-01-07T14:33:28Z Event A Logic for Reasoning about Aggregate-Combine Graph Neural Networks https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2025_schwarzentruber François Schwarzentruber (Prof., Département Informatique, LIP, ENS de Lyon) 2024-11-25T07:39:05Z Event Deep learning theory through the lens of diagonal linear networks https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_pesme Scott Pesme (post-doc in the Thoth team at Inria Grenoble) 2024-12-09T09:15:37Z Event Sliced-Wasserstein Distances and Flows on Cartan-Hadamard Manifolds https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_bonet_clement Clément Bonet (postdoctoral researcher at ENSAE/CREST) 2024-11-27T17:00:20Z Event Inertia in Optimization: Acceleration and Adaptivity https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_labarriere Hippolyte Labarriere (post-doctorat au Laboratoire d'apprentissage informatique et statistique (LCSL), University of Genova) 2024-10-10T10:11:47Z Event PnP-Flow: Plug-and-Play Image Restoration with Flow Matching https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_martin Ségolène Martin (postdoctoral researcher at TU Berlin) 2024-10-15T06:33:09Z Event Modulo Imaging: Algorithms and Applications https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_jorge_bacca Jorge Bacca (Assistant Professor, Computer Science Department, Universidad Industrial de Santander, Colombia) 2024-10-08T06:44:30Z Event Construction of low coherence unit norm tight frames https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_datta Somantika Datta (Prof, Department of Mathematics and Statistical Science , University of Idaho) 2024-09-16T09:23:26Z Event Generative Models for Blind Inverse Problems in Imaging https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_brett_levac Brett Levac (PhD student at UT Austin) 2024-09-02T14:04:22Z Event Learning of narrow neural networks in high dimensions https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_hugo_chao_cui Hugo Chao Cui (Assistant-doctorant, Laboratoire de physique statistique des systèmes computationnels) 2024-09-02T13:59:41Z Event Learning Low-rank Functions With Neural Networks https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_wilett Rebecca Willett (Professor of Statistics and Computer Science, University of Chicago) 2024-07-02T08:33:44Z Event Shaifali Parashar https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp_ Shaifali Parashar 2024-06-25T07:25:49Z Event Spectral norm estimation in deep learning https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_delattre Blaise Delattre (PHD Student - FOXSTREAM - Université Paris Dauphine - PSL) 2024-06-06T07:36:56Z Event Learning to Reconstruct From Binary Measurements Only https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_jacques Laurent Jacques (FNRS Senior Research Associate and Professor, UCLouvain, Belgium) 2024-05-21T07:54:46Z Event How to Estimate Covariance Matrices from One-Bit Samples https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_maly Johannes Maly (Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence, LMU Munich) 2024-05-16T08:12:11Z Event Yes, my deep network works! But.. what did it learn? https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_sulam Jeremias Sulam (Johns Hopkins University) 2024-05-14T11:32:22Z Event Quelques aspects mathématiques de l'analyse des Transformers https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_Letrouit Cyril Letrouit (chercheur CNRS, Laboratoire de Mathématiques d'Orsay) 2024-04-15T13:30:07Z Event A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_lebeau Hugo Lebeau (PhD Student, Université Grenoble Alpes) 2024-04-08T09:32:28Z Event Deep Learning for Fluid dynamics simulation https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_Janny Steeven Janny (PhD, INSA Lyon, LIRIS) 2024-04-02T10:13:41Z Event Theo Gnassounou (PhD candidate, Inria Saclay) https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_Gnassounou 2024-02-22T09:51:58Z Event Random matrices in optics: optical computing and computational imaging https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_Dong Jonathan Dong (post-doc EPFL) 2024-03-12T12:18:11Z Event Statistical mechanics of inference and optimization problems in high dimensions: application to spreading processes on random networks https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_Budzynski Louise Budzynski (post-doc à La Sapienza, Rome) 2024-03-03T15:22:43Z Event Leveraging Ensemble Diversity for Robust Self-Training in the presence of Sample Selection Bias https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp2024_%20Odonnat Ambroise Odonnat (ENS Paris-Saclay - MVA | Ecole Nationale des Ponts ParisTech) 2024-03-03T15:20:55Z Event An Alternative to Denoising Diffusion for Image Restoration https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/delbracio_mlsp 2024-01-09T07:40:58Z Event Graph Matching via the Projected Power Method and Mirror Descent. https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/araya_mlsp 2024-02-05T10:45:57Z Event Fatemeh Ghayyem (MIND team at Inria Paris-Saclay) https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/2024_%20Ghayyem_mlsp Exploring brain function and structure: From sparse coding to multimodal metadata analysis 2024-02-02T11:52:21Z Event Applications à l'imagerie RADAR, inversion et classification https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/gallet_mlsp Matthieu Gallet (LISTIC) 2024-01-30T11:22:46Z Event Saddle-to-Saddle Dynamics in Diagonal Linear Networks https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/pesme_mlsp Scott Pesme (PhD student at EPFL) 2024-01-22T12:09:15Z Event Learning a Graph and Importances of its Vertices https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/girault_mlsp 2024-01-10T07:50:53Z Event Learning for electron and fluorescence microscopy https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/debarnot_mlsp 2024-01-09T08:43:07Z Event Antoine Maillard (FIM (Institute for Mathematical Research) and the department of mathematics at ETH Zurich) https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_Maillard Fitting ellipsoids to random points 2023-11-17T15:00:32Z Event Camille Castera (University of Tübingen) https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_Castera_2 Near-optimal Closed-loop Method via Lyapunov Damping for Convex Optimization 2023-11-17T14:17:06Z Event Pauline Mouchès https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_Mouches CNNs and graph convolution networks for event detection in brain activity recordings of epilepsy patients 2023-11-14T08:39:59Z Event Johannes Maly https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/maly_mlsp A simple approach for quantizing neural networks 2023-10-17T13:01:28Z Event Romain Petit https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp_petit 2023-10-05T19:21:53Z Event Ludovic Stephan https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp_stephan 2023-10-05T19:41:44Z Event Tatiana Gelvez-Barrera https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp_gelvez Model-based Beamforming Method for Acoustic Imaging in Medical and Industrial Applications. 2023-10-09T08:46:51Z Event Flavien Léger https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/leger_mlsp 2023-07-12T10:12:11Z Event Luis Briceño-Arias https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp_briceno-aris-2023 Theoretical and numerical comparison of algorithms for smooth optimization 2023-09-18T19:05:06Z Event Maxime Haddouche https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp_haddouche 2023-07-12T10:11:27Z Event On the convergence of deep plug-and-play methods for image restoration https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_Hurault Samuel Hurault (PhD student at I.M.B Bordeaux) 2023-05-30T08:10:57Z Event TBA https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/copy_of_23_mlsp_saha Subhayan Saha (PhD Student in Computer Science at École Normale Supérieure de Lyon) 2023-04-03T12:22:48Z Event Low-dimensional representations for Stochastic Gradient Descent https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/23_mlsp_stephan Ludovic Stéphan (postdoctoral student in the IdePHICS lab at EPFL) 2023-05-09T07:27:22Z Event A Bayesian Approach for Multivariate Multifractal Analysis https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp_leon23 Lorena León, CREATIS 2023-04-27T12:59:51Z Event Bayesian inference with generative priors encoded by neural networks https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/pereyra_mlsp Marcelo Pereyra (Associate Professor at Heriot-Watt University) 2023-04-20T10:33:40Z Event Modeling Brain Waveforms with Convolutional Dictionary Learning and Point Processes https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_moreau Thomas Moreau (INRIA Saclay) 2023-04-24T09:09:51Z Event On the Robustness of Text Vectorizers https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/23_mlsp_garreau Damien Garreau (MCF at J. A. Dieudonné laboratory, Université Côte d'Azur). 2023-04-21T15:44:12Z Event Towards parameter-free (strongly convex) FISTA via adaptive backtracking and restart https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_%20Calatroni Luca Calatroni (CNRS researcher in the Morpheme team at the I3S laboratory in Sophia-Antipolis, France) 2023-02-19T19:46:04Z Event Non smooth implicit differentiation https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_Silveti-Falls Tony Silveti-Falls (CentraleSupélec/University of Paris-Saclay) 2023-04-04T08:02:29Z Event Learning of latent spaces dedicated to the segmentation of medical images https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_OlivierBernard Olivier Bernard (CREATIS) 2023-04-04T08:02:00Z Event Universal approximation with neural networks through the lens of computability https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_Thesing Laura Thesing (Postdoctoral researcher - LMU Munich) 2023-03-17T08:11:29Z Event Learning Activation Functions in Neural Networks https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_Bohra Pakshal Bohra (PhD Student, EPFL, with M. Unser) 2023-03-10T14:53:49Z Event Hypersphere Fitting: Model, Algorithms and Future Work https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_tourneret Jean-Yves Tourneret (Professeur à l'INP-ENSEEIHT, Toulouse) 2023-03-06T16:08:52Z Event Harnessing complexity in photonics for neuromorphic computing and security applications https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_Pavanello Fabio Pavanello (CR CNRS, Lyon Institute of Nanotechnology (INL)) 2023-01-31T14:56:12Z Event Learning Graphical Factor Models with Riemannian Optimization https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_Breloy Arnaud Breloy (associate professor at University Paris Nanterre and the LEME laboratory) 2023-02-21T08:34:40Z Event Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_Huizing Geert-Jan Huizing (PhD student at École normale supérieure PSL) 2023-01-23T10:42:08Z Event Second-order inertial algorithms for very large-scale optimization https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp23_Castera Camille Castera (postdoc at the University of Tübingen) 2023-01-16T09:34:02Z Event Sparsification of the regularized magnetic Laplacian with multi-type spanning forests https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_%20Fanuel Michaël Fanuel (CNRS postdoc at CRIStAL in the SigMA team in Lille) 2022-11-08T10:28:19Z Event Plug-and-Play Models for Large-Scale Computational Imaging https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Kamilov Ulugbek S. Kamilov (Washington University, St. Louis) 2022-12-05T09:09:17Z Event Graph Neural Networks with Precomputed Features https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_chepuri Sundeep Prabhakar Chepuri (Indian Institue of Science, Bangalore) 2022-12-05T08:54:40Z Event Neural networks beyond explainability: selective inference for sequence motifs https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Villie Antoine Villie (PhD student, LBBE, Lyon) 2022-11-08T10:26:38Z Event A new clustering approach for directed graphs https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Sevi Harry Sevi (post-doc, ENS Paris-Saclay, Centre Borelli)) 2022-11-14T08:35:28Z Event TBA https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Besancon Mathieu Besançon (Zuse Institute Berlin, in the AI in Society, Science, and Technology department) 2022-11-08T10:25:56Z Event Variational approaches for signal and image processing https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_SiSyPhe One-day workshop 2022-11-16T20:11:26Z Event Law of large numbers and central limit theorem for wide two-layer neural networks: the mini-batch and noisy case https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Descours Arnaud Descours (PhD student, LMBP, Université Clermond Auvergne) 2022-11-14T08:33:34Z Event TBA https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Bareilles Gilles Bareilles (PhD student, LJK, Université Grenoble Alpes) 2022-09-13T07:29:46Z Event Removing speckle in SAR images while maintaining spatial resolution: from classical image processing techniques to unsupervised deep learning https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/From%20classical%20image%20processing%20techniques%20to%20unsupervised%20deep%20learning Loïc Denis (Professor Université de Saint-Etienne, Laboratoire Hubert Curien) 2022-09-19T07:27:26Z Event Generalized time-frequency transforms and their zeros https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Pascal Barbara Pascal (postdoctoral researcher à CRIStAL, SigMA team, Lille 2022-09-19T08:06:58Z Event Outils mathématiques et de traitement du signal pour l’étude polarimétrique des ondes gravitationnelles https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Cano Cyril Cano (PhD Student, GIPSA-lab, Grenoble ; encadrants : N. Le Bihan et E. Chassande-Mottin) 2022-09-15T15:52:46Z Event Learning from incomplete features by simultaneous training of neural networks and sparse coding https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Caiafa Séminaire reporté ; Cesar Caiafa (Independent Researcher at CONICET - Adjunct Professor at University of Buenos Aires) 2022-09-12T09:11:32Z Event Limites de résolution du problème de déconvolution de sources ponctuelles https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Ferreira_Da_Costa Maxime Ferreira Da Costa (research associate in the Department of Electrical and Computer Engineering, University of Southern California) 2022-06-27T12:17:58Z Event Machine Learning for Single-Cell Biology https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Picard Franck Picard (DR CNRS, LBMC) 2022-06-14T08:10:33Z Event Multivariate Normality Test for the detection of Weak Tremors https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/copy_of_mlsp22_El_Bouch Sara El Bouch (PhD Student, GIPSA-lab, Grenoble ; encadrants : Olivier Michel et Pierre Comon) 2022-06-14T08:08:33Z Event 2 talks: "Graph Neural Networks on Large Random Graphs: Convergence, Stability, Universality" and "Sélection d'hyperparamètres via la différentiation algorithmique" https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Vaiter_Keriven Nicolas Keriven (CNRS, Gipsa) et Samuel Vaiter (CNRS, Université Côte d'Azur) 2022-06-16T08:57:26Z Event Wilson’s Algorithm for Randomized Linear Algebra https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Pilavci Yusuf Yigit Pilavci (PhD Student, GIPSA-lab, Grenoble ; encadrants : Pierre-Olivier Amblard ; Nicolas Tremblay ; Simon Barthelmé) 2022-06-07T12:58:44Z Event Heat diffusion distance processes for graphs and their application to distribution shift detection https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Lasalle Etienne Lasalle (PhD Student, Laboratoire de Mathématiques - Université Paris-Saclay - Orsay) 2022-06-07T09:11:03Z Event Kernel approximations using determinantal point processes https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Belhadji Ayoub Belhadji (post-doc, LIP, ENS de Lyon) 2022-05-16T11:30:13Z Event Sum of squares with Reproducing Kernel Hilbert Spaces, a path to global optimisation of regular functions https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Marteau-Ferey Ulysse Marteau-Ferey (PhD, DI, ENS Paris) 2022-05-09T20:43:36Z Event Deep unfolding network for image restoration by quantum interactive patches https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Basarab Adrian Basarab (Prof Univ.Lyon 1; CREATIS) 2022-05-09T20:39:57Z Event Optimal ecological transition path using MMK formulation https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Lage Clara Lage (post-doc, Ecole Polytechnique, Paris) 2022-05-02T12:41:15Z Event (Reporté) Test non-paramétrique de comparaison d'échantillon basé sur les méthodes a noyaux: application au Single-Cell RNA sequencing https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/copy_of_mlsp22_Ozier-Lafontaine Anthony Ozier-Lafontaine (Laboratoire de Mathématiques Jean Leray. Université de Nantes) 2022-04-21T07:53:43Z Event Optimal Transport for Unsupervised Graph Representation Learning https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_Vincent_Cuaz Cédric Vincent-Cuaz (PhD candidate, Univ Nice) 2022-04-20T09:26:46Z Event Deep reconstruction methods for computational hyperspectral imaging https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_%20ducros Nicolas Ducros (INSA de Lyon, CREATIS) 2022-04-11T08:50:01Z Event Mini meeting "Machine Learning and sampling methods for climate and physics" https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_%20Climate_Learning Ronan Fablet (IMT Atlantique) ; Tom Beucler (UNIL, Lausanne) ; Manon Michel (UCA) ; Davide Feranda (LSCE, IPSL) ; George Miloshevich (ENSL, CNRS) 2022-04-04T11:56:24Z Event A Probabilistic Graph Coupling View of Dimension Reduction https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_%20VanAssel Hugues Van Assel (UMPA, ENS de Lyon) 2022-03-25T08:31:44Z Event The Seriation and 1D-localization problems in latent space models. https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_%20Issartel Yann Issartel (post doc CREST) 2022-02-11T14:38:05Z Event Evaluation and comparison of graph statistical models https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_%20Duvivier Louis Duvivier (ATER LIRIS & INSA de Lyon) 2022-02-10T20:13:21Z Event Robustness via distributional dynamic programming https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp22_%20Achab Mastane Achab (coming from post-doc at Universitat Pompeu Fabra) 2022-02-11T14:37:17Z Event Divergences for Implicit Generative Models. https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_%20Arbel Michael Arbel (post-doc à Grenoble, équipe J. Mairal) 2021-12-14T07:53:15Z Event Sur l'analyse statistique et algorithmique des problèmes inverses avec des signaux générés par réseaux de neurones aléatoires https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Loueiro Bruno Loueiro (Post-doc, EPFL) 2021-11-16T15:15:01Z Event Learnable Discrete Wavelet Transform for Data-Adapted Time-Frequency Representations https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Frusque Gaetan Frusque (post-doc ETH Zurich) 2021-11-16T15:13:51Z Event Quantized Compressive Learning: from broad intuitions to precise guarantees https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_%20Schellekens Vincent Schellekens (Inria, Dante - OCKHAM, LIP) 2021-11-15T08:47:29Z Event TBA https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Debarre Thomas Debarre (PhD candidate, EPFL) 2021-07-13T08:53:01Z Event Few-Shot Learning on Graph-Structured Data: the Case of Brain Activation Maps https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Bontonou Myriam Bontonou (PhD candidate, IMT Atlantique, Lab-STICC) 2021-06-28T20:19:49Z Event Structured Toeplitz matrices to build compact and secure neural networks https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Araujo Alexandre ARAUJO (Université Paris-Dauphine PSL) 2021-06-17T21:07:58Z Event Contextual anomalies in graphs, detection and explanation https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Vaudaine Rémi Vaudaine (Laboratoire Hubert Curien, Saint-Etienne) 2021-06-21T20:14:14Z Event Statistical foundations of stochastic neighbor embedding https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Picard Franck Picard (CNRS, LBMC, ENS de Lyon) 2021-05-19T15:49:52Z Event Learning with Low-rank Approximations https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Cohen Jérémy Cohen (CNRS, IRISA, équipe PANAMA, Rennes) 2021-05-04T11:57:30Z Event Leaving the Euclidean Norm in GSP: Theory, Applications and Perspectives https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Girault Benjamin Girault (enseignant-chercheur ENSAI, Rennes) 2021-04-06T11:46:59Z Event Adaptive large-scale graph signal denoising https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Navarro Fabien Navarro (enseignant-chercheur ENSAI, Rennes) 2021-03-29T08:13:28Z Event Incorporating expert feedback into anomaly detection using support vector machines https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Lesouple Julien Lesouple (Post-doc fellow at TESA Laboratory) 2021-03-01T15:39:15Z Event Traitement morphologique et logarithmique d’images acquises sous éclairement variable https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Noyel Guillaume Noyel (Research Director, International Prevention Research Institute, Dardilly (Métropole de Lyon), France 2021-02-22T09:54:18Z Event Optimal transport problemS for graphS learning https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Vayer Titouan Vayer (post-doctorant equipe inria DANTE ; ENS Lyon) 2021-02-22T09:02:53Z Event Forecast of Extreme Heatwaves using Deep Learning https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_JacqueDumas Valerian Jacques-Dumas (étudiant ENSL, PLR équipe SISYPHE, Labo Physique, ENS Lyon) 2021-03-01T15:42:27Z Event Analysis of complex physical systems with information theory and statistical learning https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Seydoux Léonard Seydoux (post-doctorant ISTerre, Grenoble) 2021-02-23T12:16:35Z Event Graph-based latent space analysis https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Lassance Carlos Lassance (post-doctorant naverlabs.com ; Grenoble) 2021-02-22T09:00:20Z Event Leveraging Global Parameters for Flow-based Neural Posterior Estimation https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_Rodrigues Pedro L. C. Rodrigues (post-doctorant équipe Parietal, INRIA-Saclay) 2021-02-05T09:10:48Z Event The Bethe-Hessian matrix for community detection in static and dynamical sparse graphs https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21-DallAmico Lorenzo Dall'Amico (doctorant GIPSA-lab, Grenoble) 2021-01-25T08:31:18Z Event TV- based methods for sparse reconstruction in continuous-domain https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp-fageot Julien Fageot (post-doctorant à McGill University) 2021-02-05T14:54:39Z Event Feature-space selection in voxelwise encoding models with banded ridge regression https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/mlsp21_DupreLaTour Tom Dupré la Tour (post-doctorant, Univ. Berkeley, CA, USA) 2021-01-20T15:46:55Z Event Efficacité de l'optimisation convexe pour le traitement du signal et la science des données https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/MLSP-cosse Augustin Cosse (post-doctorant ENS Paris) 2021-01-25T08:06:14Z Event Maximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/copy2_of_statistical-maximum-entropy-models-for-turbulence-generation Valentin De Bortoli (post-doctorant, Univ Oxford) 2021-01-20T15:47:19Z Event Fast resolution resolution of structured inverse problems: extrapolation and iterative regularization https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/MLSP-massias Mathurin Massias (post-doctorant à l'Université de Gènes) 2021-04-13T16:13:48Z Event Statistical maximum-entropy models for turbulence generation https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/statistical-maximum-entropy-models-for-turbulence-generation Sixin Zhang (IRIT, Université de Toulouse) 2020-12-03T17:34:07Z Event Un point sur les réseaux à poids quantifiés https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/2020-11-10-Malgouyres François Malgouyres (IMT, Toulouse) 2020-11-19T10:11:04Z Event Computational imaging: from applications to theory https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/2020-11-13-Tachella Julian Tachella (School of Engineering, University of Edinburgh en post-doc avec Mike Davies) 2020-10-27T12:15:50Z Event Object detection, characterization and reconstructionfrom faint signals in images: applications in astronomy and microscopy https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/olivier-flasseur Olivier Flasseur (Université de Lyon, Université Lyon1, ENS de Lyon, CNRS, Centre de Recherche Astrophysique de Lyon UMR 5574, F-69230, Saint-Genis-Laval, France) 2020-10-27T10:50:51Z Event Second order optimization methods for the solution of large scale nonlinear noisy problems https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/2020-11-10-Riccietti Elisa Riccietti (Maitre de Conférence ENS de Lyon, membre de l’équipe Dante du LIP) 2020-10-08T11:48:25Z Event Link predictions https://www.ens-lyon.fr/PHYSIQUE/seminars/machine-learning-and-signal-processing/quentin-duchemin Quentin Duchemin (U. Paris-Est Marne-la-Vallée) 2020-10-06T12:58:19Z Event