Machine Learning and Signal Processing
Past Machine Learning and Signal Processing seminars
Somantika Datta
Somantika Datta (Prof, Department of Mathematics and Statistical Science , University of Idaho)Construction of low coherence unit norm tight frames
16/09/2024 de 13:00 à 14:00
Brett Levac
Brett Levac (PhD student at UT Austin)Generative Models for Blind Inverse Problems in Imaging
03/09/2024 de 13:00 à 14:00
Hugo Chao Cui
Hugo Chao Cui (Assistant-doctorant, Laboratoire de physique statistique des systèmes computationnels)Learning of narrow neural networks in high dimensions
23/07/2024 de 13:00 à 14:00
Rebecca Willett
Rebecca Willett (Professor of Statistics and Computer Science, University of Chicago)Learning Low-rank Functions With Neural Networks
02/07/2024 de 13:00 à 14:00
Blaise Delattre
Blaise Delattre (PHD Student - FOXSTREAM - Université Paris Dauphine - PSL)Spectral norm estimation in deep learning
06/06/2024 de 13:00 à 14:00
Laurent Jacques
Laurent Jacques (FNRS Senior Research Associate and Professor, UCLouvain, Belgium)Learning to Reconstruct From Binary Measurements Only
21/05/2024 de 13:00 à 14:00
Johannes Maly
Johannes Maly (Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence, LMU Munich)How to Estimate Covariance Matrices from One-Bit Samples
16/05/2024 de 13:00 à 14:00
Jeremias Sulam
Jeremias Sulam (Johns Hopkins University)Yes, my deep network works! But.. what did it learn?
14/05/2024 de 15:00 à 16:00
Cyril Letrouit
Cyril Letrouit (chercheur CNRS, Laboratoire de Mathématiques d'Orsay)Quelques aspects mathématiques de l'analyse des Transformers
16/04/2024 de 13:00 à 14:00
Hugo Lebeau
Hugo Lebeau (PhD Student, Université Grenoble Alpes)A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation
09/04/2024 de 13:00 à 14:00
Steeven Janny
Steeven Janny (PhD, INSA Lyon, LIRIS)Deep Learning for Fluid dynamics simulation
02/04/2024 de 13:00 à 14:00
Jonathan Dong
Jonathan Dong (post-doc EPFL)Random matrices in optics: optical computing and computational imaging
19/03/2024 de 13:00 à 14:00
Louise Budzynski
Louise Budzynski (post-doc à La Sapienza, Rome)Statistical mechanics of inference and optimization problems in high dimensions: application to spreading processes on random networks
12/03/2024 de 13:00 à 14:00
Ambroise Odonnat
Ambroise Odonnat (ENS Paris-Saclay - MVA | Ecole Nationale des Ponts ParisTech)Leveraging Ensemble Diversity for Robust Self-Training in the presence of Sample Selection Bias
05/03/2024 de 13:00 à 14:00
Mauricio Delbracio
An Alternative to Denoising Diffusion for Image Restoration
13/02/2024 de 04:30 à 05:30
Ernesto Araya Valdivia
Graph Matching via the Projected Power Method and Mirror Descent.
06/02/2024 de 13:00 à 14:00
Fatemeh Ghayyem
Exploring brain function and structure: From sparse coding to multimodal metadata analysisFatemeh Ghayyem (MIND team at Inria Paris-Saclay)
05/02/2024 de 13:00 à 14:00
Matthieu Gallet
Matthieu Gallet (LISTIC)Applications à l'imagerie RADAR, inversion et classification
30/01/2024 de 01:00 à 02:00
Scott Pesme
Scott Pesme (PhD student at EPFL)Saddle-to-Saddle Dynamics in Diagonal Linear Networks
16/01/2024 de 01:00 à 02:00
Antoine Maillard
Fitting ellipsoids to random pointsAntoine Maillard (FIM (Institute for Mathematical Research) and the department of mathematics at ETH Zurich)
22/11/2023 de 13:00 à 14:00 — M7 101
Camille Castera
Near-optimal Closed-loop Method via Lyapunov Damping for Convex OptimizationCamille Castera (University of Tübingen)
21/11/2023 de 13:00 à 14:00 — M7 101
Pauline Mouchès
CNNs and graph convolution networks for event detection in brain activity recordings of epilepsy patientsPauline Mouchès
14/11/2023 de 14:00 à 15:00 — MGN1 105
Johannes Maly
A simple approach for quantizing neural networksJohannes Maly
31/10/2023 de 01:00 à 02:00
Tatiana Gelvez-Barrera
Model-based Beamforming Method for Acoustic Imaging in Medical and Industrial Applications.Tatiana Gelvez-Barrera
10/10/2023 de 01:00 à 02:00
Luis Briceño-Arias
Theoretical and numerical comparison of algorithms for smooth optimizationLuis Briceño-Arias
19/09/2023 de 13:00 à 14:00
Samuel Hurault
Samuel Hurault (PhD student at I.M.B Bordeaux)On the convergence of deep plug-and-play methods for image restoration
20/06/2023 de 13:00 à 14:00
Subhayan Saha
Subhayan Saha (PhD Student in Computer Science at École Normale Supérieure de Lyon)TBA
16/05/2023 de 13:00 à 14:00
Ludovic Stéphan
Ludovic Stéphan (postdoctoral student in the IdePHICS lab at EPFL)Low-dimensional representations for Stochastic Gradient Descent
09/05/2023 de 13:00 à 14:00
Lorena Léon
Lorena León, CREATISA Bayesian Approach for Multivariate Multifractal Analysis
02/05/2023 de 01:00 à 02:00
Marcelo Pereyra
Marcelo Pereyra (Associate Professor at Heriot-Watt University)Bayesian inference with generative priors encoded by neural networks
26/04/2023 de 01:00 à 02:00
Thomas Moreau
Thomas Moreau (INRIA Saclay)Modeling Brain Waveforms with Convolutional Dictionary Learning and Point Processes
25/04/2023 de 13:00 à 14:00
Damien Garreau
Damien Garreau (MCF at J. A. Dieudonné laboratory, Université Côte d'Azur).On the Robustness of Text Vectorizers
18/04/2023 de 13:00 à 14:00
Luca Calatroni
Luca Calatroni (CNRS researcher in the Morpheme team at the I3S laboratory in Sophia-Antipolis, France)Towards parameter-free (strongly convex) FISTA via adaptive backtracking and restart
11/04/2023 de 13:00 à 14:00
Tony Silveti-Falls
Tony Silveti-Falls (CentraleSupélec/University of Paris-Saclay)Non smooth implicit differentiation
04/04/2023 de 14:00 à 15:00
Olivier Bernard
Olivier Bernard (CREATIS)Learning of latent spaces dedicated to the segmentation of medical images
04/04/2023 de 13:00 à 14:00
Laura Thesing
Laura Thesing (Postdoctoral researcher - LMU Munich)Universal approximation with neural networks through the lens of computability
21/03/2023 de 13:00 à 14:00
Pakshal Bohra
Pakshal Bohra (PhD Student, EPFL, with M. Unser)Learning Activation Functions in Neural Networks
14/03/2023 de 01:00 à 02:00
Jean-Yves Tourneret
Jean-Yves Tourneret (Professeur à l'INP-ENSEEIHT, Toulouse)Hypersphere Fitting: Model, Algorithms and Future Work
07/03/2023 de 01:00 à 02:00
Fabio Pavanello
Fabio Pavanello (CR CNRS, Lyon Institute of Nanotechnology (INL))Harnessing complexity in photonics for neuromorphic computing and security applications
28/02/2023 de 13:00 à 14:00
Arnaud Breloy
Arnaud Breloy (associate professor at University Paris Nanterre and the LEME laboratory)Learning Graphical Factor Models with Riemannian Optimization
21/02/2023 de 13:00 à 14:00
Geert-Jan Huizing
Geert-Jan Huizing (PhD student at École normale supérieure PSL)Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors
24/01/2023 de 13:00 à 14:00
Camille Castera
Camille Castera (postdoc at the University of Tübingen)Second-order inertial algorithms for very large-scale optimization
10/01/2023 de 13:00 à 14:00
Michaël Fanuel
Michaël Fanuel (CNRS postdoc at CRIStAL in the SigMA team in Lille)Sparsification of the regularized magnetic Laplacian with multi-type spanning forests
13/12/2022 de 13:00 à 14:00
Ulugbek S. Kamilov
Ulugbek S. Kamilov (Washington University, St. Louis)Plug-and-Play Models for Large-Scale Computational Imaging
09/12/2022 de 10:30 à 11:30
Sundeep Prabhakar Chepuri
Sundeep Prabhakar Chepuri (Indian Institue of Science, Bangalore)Graph Neural Networks with Precomputed Features
06/12/2022 de 13:00 à 14:00
Antoine Villie
Antoine Villie (PhD student, LBBE, Lyon)Neural networks beyond explainability: selective inference for sequence motifs
29/11/2022 de 13:00 à 14:00
Harry Sevi
Harry Sevi (post-doc, ENS Paris-Saclay, Centre Borelli))A new clustering approach for directed graphs
22/11/2022 de 13:00 à 14:00
Mathieu Besançon
Mathieu Besançon (Zuse Institute Berlin, in the AI in Society, Science, and Technology department)TBA
21/11/2022 de 13:30 à 14:30
Barbara Pascal / Audrey Repetti / Julian Tachella / Titouan Vayer
One-day workshopVariational approaches for signal and image processing
18/11/2022 de 10:00 à 17:00
Arnaud Descours
Arnaud Descours (PhD student, LMBP, Université Clermond Auvergne)Law of large numbers and central limit theorem for wide two-layer neural networks: the mini-batch and noisy case
15/11/2022 de 13:00 à 14:00
Gilles Bareilles
Gilles Bareilles (PhD student, LJK, Université Grenoble Alpes)TBA
25/10/2022 de 13:00 à 14:00
Loïc Denis
Loïc Denis (Professor Université de Saint-Etienne, Laboratoire Hubert Curien)Removing speckle in SAR images while maintaining spatial resolution: from classical image processing techniques to unsupervised deep learning
11/10/2022 de 01:00 à 02:00
Barbara Pascal
Barbara Pascal (postdoctoral researcher à CRIStAL, SigMA team, LilleGeneralized time-frequency transforms and their zeros
28/09/2022 de 02:00 à 03:00
Cyril Cano
Cyril Cano (PhD Student, GIPSA-lab, Grenoble ; encadrants : N. Le Bihan et E. Chassande-Mottin)Outils mathématiques et de traitement du signal pour l’étude polarimétrique des ondes gravitationnelles
27/09/2022 de 13:00 à 14:00
Cesar Caiafa
Séminaire reporté ; Cesar Caiafa (Independent Researcher at CONICET - Adjunct Professor at University of Buenos Aires)Learning from incomplete features by simultaneous training of neural networks and sparse coding
13/09/2022 de 13:00 à 14:00
Maxime Ferreira Da Costa
Maxime Ferreira Da Costa (research associate in the Department of Electrical and Computer Engineering, University of Southern California)Limites de résolution du problème de déconvolution de sources ponctuelles
29/06/2022 de 13:00 à 14:00
Franck Picard
Franck Picard (DR CNRS, LBMC)Machine Learning for Single-Cell Biology
28/06/2022 de 13:00 à 14:00
Sara El Bouch
Sara El Bouch (PhD Student, GIPSA-lab, Grenoble ; encadrants : Olivier Michel et Pierre Comon)Multivariate Normality Test for the detection of Weak Tremors
21/06/2022 de 13:00 à 14:00
Nicolas Keriven ; Samuel Vaiter
Nicolas Keriven (CNRS, Gipsa) et Samuel Vaiter (CNRS, Université Côte d'Azur)2 talks: "Graph Neural Networks on Large Random Graphs: Convergence, Stability, Universality" and "Sélection d'hyperparamètres via la différentiation algorithmique"
17/06/2022 de 13:00 à 14:30
Yusuf Yigit Pilavci
Yusuf Yigit Pilavci (PhD Student, GIPSA-lab, Grenoble ; encadrants : Pierre-Olivier Amblard ; Nicolas Tremblay ; Simon Barthelmé)Wilson’s Algorithm for Randomized Linear Algebra
09/06/2022 de 13:00 à 15:00
Etienne Lasalle
Etienne Lasalle (PhD Student, Laboratoire de Mathématiques - Université Paris-Saclay - Orsay)Heat diffusion distance processes for graphs and their application to distribution shift detection
07/06/2022 de 13:00 à 14:00
Ayoub Belhadji
Ayoub Belhadji (post-doc, LIP, ENS de Lyon)Kernel approximations using determinantal point processes
17/05/2022 de 13:00 à 14:00
Ulysse Marteau-Ferey
Ulysse Marteau-Ferey (PhD, DI, ENS Paris)Sum of squares with Reproducing Kernel Hilbert Spaces, a path to global optimisation of regular functions
12/05/2022 de 10:00 à 11:00
Adrian Basarab
Adrian Basarab (Prof Univ.Lyon 1; CREATIS)Deep unfolding network for image restoration by quantum interactive patches
10/05/2022 de 13:00 à 14:00
Clara Lage
Clara Lage (post-doc, Ecole Polytechnique, Paris)Optimal ecological transition path using MMK formulation
03/05/2022 de 13:00 à 14:00
Anthony Ozier-Lafontaine
Anthony Ozier-Lafontaine (Laboratoire de Mathématiques Jean Leray. Université de Nantes)(Reporté) Test non-paramétrique de comparaison d'échantillon basé sur les méthodes a noyaux: application au Single-Cell RNA sequencing
26/04/2022 de 13:00 à 14:00
Cédric Vincent-Cuaz
Cédric Vincent-Cuaz (PhD candidate, Univ Nice)Optimal Transport for Unsupervised Graph Representation Learning
19/04/2022 de 13:00 à 14:00
Nicolas Ducros
Nicolas Ducros (INSA de Lyon, CREATIS)Deep reconstruction methods for computational hyperspectral imaging
12/04/2022 de 13:00 à 14:00
"Machine Learning and sampling methods for climate and physics"
Ronan Fablet (IMT Atlantique) ; Tom Beucler (UNIL, Lausanne) ; Manon Michel (UCA) ; Davide Feranda (LSCE, IPSL) ; George Miloshevich (ENSL, CNRS)Mini meeting "Machine Learning and sampling methods for climate and physics"
du 04/04/2022 13:30 au 05/04/2022 17:30
Hugues Van Assel
Hugues Van Assel (UMPA, ENS de Lyon)A Probabilistic Graph Coupling View of Dimension Reduction
29/03/2022 de 13:00 à 14:00
Yann Issartel
Yann Issartel (post doc CREST)The Seriation and 1D-localization problems in latent space models.
08/03/2022 de 13:00 à 14:00
Louis Duvivier
Louis Duvivier (ATER LIRIS & INSA de Lyon)Évaluation de modèles statistiques de graphes : au-delà du principe d'entropie minimale.
01/03/2022 de 13:00 à 14:00
Mastane Achab
Mastane Achab (coming from post-doc at Universitat Pompeu Fabra)Robustness via distributional dynamic programming
15/02/2022 de 13:00 à 14:00
Michael Arbel
Michael Arbel (post-doc à Grenoble, équipe J. Mairal)Divergences for Implicit Generative Models.
16/12/2021 de 11:30 à 12:30
Bruno Loueiro
Bruno Loueiro (Post-doc, EPFL)Sur l'analyse statistique et algorithmique des problèmes inverses avec des signaux générés par réseaux de neurones aléatoires
22/11/2021 de 16:00 à 17:00
Gaetan Frusque
Gaetan Frusque (post-doc ETH Zurich)Learnable Discrete Wavelet Transform for Data-Adapted Time-Frequency Representations
16/11/2021 de 16:00 à 17:00
Vincent Schellekens
Vincent Schellekens (Inria, Dante - OCKHAM, LIP)Quantized Compressive Learning: from broad intuitions to precise guarantees
15/11/2021 de 16:00 à 17:00
Myriam Bontonou
Myriam Bontonou (PhD candidate, IMT Atlantique, Lab-STICC)Few-Shot Learning on Graph-Structured Data: the Case of Brain Activation Maps
05/07/2021 de 15:00 à 16:00
Alexandre ARAUJO
Alexandre ARAUJO (Université Paris-Dauphine PSL)Structured Toeplitz matrices to build compact and secure neural networks
01/07/2021 de 15:45 à 16:45
Rémi Vaudaine
Rémi Vaudaine (Laboratoire Hubert Curien, Saint-Etienne)Contextual anomalies in graphs, detection and explanation
24/06/2021 de 13:00 à 14:00
Franck Picard
Franck Picard (CNRS, LBMC, ENS de Lyon)Statistical foundations of stochastic neighbor embedding
20/05/2021 de 10:00 à 11:00
Jérémy Cohen
Jérémy Cohen (CNRS, IRISA, équipe PANAMA, Rennes)Learning with Low-rank Approximations
06/05/2021 de 10:00 à 11:00
Benjamin Girault
Benjamin Girault (enseignant-chercheur ENSAI, Rennes)Leaving the Euclidean Norm in GSP: Theory, Applications and Perspectives
06/04/2021 de 15:00 à 16:00
Fabien Navarro
Fabien Navarro (enseignant-chercheur ENSAI, Rennes)Adaptive large-scale graph signal denoising
30/03/2021 de 14:00 à 15:00
Julien Lesouple
Julien Lesouple (Post-doc fellow at TESA Laboratory)Incorporating expert feedback into anomaly detection using support vector machine
25/03/2021 de 13:00 à 14:00
Guillaume Noyel
Guillaume Noyel (Research Director, International Prevention Research Institute, Dardilly (Métropole de Lyon), FranceTraitement morphologique et logarithmique d’images acquises sous éclairement variable
11/03/2021 de 10:00 à 11:00
Titouan Vayer
Titouan Vayer (post-doctorant equipe inria DANTE ; ENS Lyon)Optimal transport problemS for graphS learning
04/03/2021 de 14:30 à 15:30
Valerian Jacques-Dumas
Valerian Jacques-Dumas (étudiant ENSL, PLR équipe SISYPHE, Labo Physique, ENS Lyon)Forecast of Extreme Heatwaves using Deep Learning
02/03/2021 de 14:00 à 15:00
Léonard Seydoux
Léonard Seydoux (post-doctorant ISTerre, Grenoble)Analysis of complex physical systems with information theory and statistical learning
02/03/2021 de 10:00 à 11:00
Carlos Lassance
Carlos Lassance (post-doctorant naverlabs.com ; Grenoble)Graph-based latent space analysis
26/02/2021 de 14:30 à 15:30
Pedro L.C. Rodrigues
Pedro L. C. Rodrigues (post-doctorant équipe Parietal, INRIA-Saclay)Leveraging Global Parameters for Flow-based Neural Posterior Estimation
25/02/2021 de 10:00 à 11:00
Lorenzo Dall'Amico
Lorenzo Dall'Amico (doctorant GIPSA-lab, Grenoble)The Bethe-Hessian matrix for community detection in static and dynamical sparse graphs
09/02/2021 de 14:00 à 15:00
Julien Fageot
Julien Fageot (post-doctorant à McGill University)TV- based methods for sparse reconstruction in continuous-domain
08/02/2021 de 10:30 à 11:30
Tom Dupré la Tour
Tom Dupré la Tour (post-doctorant, Univ. Berkeley, CA, USA)Feature-space selection in voxelwise encoding models with banded ridge regression
03/02/2021 de 18:00 à 19:00
Augustin Cosse
Augustin Cosse (post-doctorant ENS Paris)Efficacité de l'optimisation convexe pour le traitement du signal et la science des données
01/02/2021 de 14:30 à 15:30
Valentin De Bortoli
Valentin De Bortoli (post-doctorant, Univ Oxford)Maximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach
28/01/2021 de 14:30 à 15:30
Mathurin Massias
Mathurin Massias (post-doctorant à l'Université de Gènes)Fast resolution resolution of structured inverse problems: extrapolation and iterative regularization
14/01/2021 de 16:00 à 17:00
Sixin Zhang
Sixin Zhang (IRIT, Université de Toulouse)Statistical maximum-entropy models for turbulence generation
10/12/2020 de 09:30 à 10:30
François Malgouyres
François Malgouyres (IMT, Toulouse)Un point sur les réseaux à poids quantifiés
24/11/2020 de 09:00 à 10:00 — Visio : https://ent-services.ens-lyon.fr/entVisio/quickjoin.php?hash=1321750ebd942062258b637f58c2209ddc6914e2a30297dd506c365d4c780fa3&meetingID=2481
Julian Tachella
Julian Tachella (School of Engineering, University of Edinburgh en post-doc avec Mike Davies)Computational imaging: from applications to theory
13/11/2020 de 14:30 à 15:30 — M7 101
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)Object detection, characterization and reconstructionfrom faint signals in images: applications in astronomy and microscopy
30/10/2020 de 10:30 à 11:30 — R 116 (GN1 Monod)
Elisa Riccietti
Elisa Riccietti (Maitre de Conférence ENS de Lyon, membre de l’équipe Dante du LIP)Second order optimization methods for the solution of large scale nonlinear noisy problems
14/10/2020 de 11:00 à 12:00 — Salle de réunion du LIP, M7-316, ENS de Lyon, Site Monod
Quentin Duchemin
Quentin Duchemin (U. Paris-Est Marne-la-Vallée)Link predictions
08/10/2020 de 10:00 à 11:00 — Salle de réunion M7 du LIP - 3e étage
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