With PhD students, postdocs, and associated researchers, we organize weekly seminars - currently only online. In this weekly group meeting, we alternate presentations by invited researchers on the topics of missing data, causal inference but also ML/statistics in general, with presentations by students of the group and also paper reading sessions.
Here you can find a list of group meetings with abstracts. We regularly update the links and list of confirmed speakers. Please contact Bénédicte Colnet or Pan Zhao if you are interested to get the slides or if you want to visit us or to receive the announcement for the talks.
See below the calendar for more details.
2023-03-29, Gaël Varoquaux, Research director at Inria, France: Machine learning for health and society? Progress and vision.
2023-03-20, Mike Van Ness, PhD student at Stanford University, USA: The Missing Indicator Method: From Low to High Dimensions.
2023-03-13, Pan Zhao, PhD student at Inria, France: Efficient and robust transfer learning of optimal individualized treatment regimes with right-censored survival data.
2023-03-06, Margaux Zaffran, PhD student at Inria, France: Conformal Prediction with Missing Values.
2023-02-27, Lola Etievant, Postdoctoral fellow at National Cancer Institute, USA: Cox model inference for relative hazard and pure risk from stratified weight-calibrated case-cohort data.
2023-02-22, Guillaume Martin, MD and PhD student at Sorbonne Université, France: Meta-analyses, heterogeneity, and meta-epidemiology.
2023-02-13, Eric Dunipace, MD student at David Geffen School of Medicine at UCLA, USA: Optimal transport weights for causal inference.
2023-01-18, Kat Hoffman, Senior Data Analyst at Columbia University Medical Center, USA: Comparison of a Target Trial Emulation Framework vs Model-First Approaches to Estimate the Effect of Corticosteroids on COVID-19 Mortality.
2023-01-09, Daisy Ding, PhD student at Stanford University, USA: Cooperative learning for multiview analysis.
2023-01-04, Linus Bleistein, PhD student at Inria, France: Learning the dynamics of sparsely observed interacting systems.
2022-11-30, Xiao Wu, Postdoc at Stanford University, USA: Assessing the causal effects of a stochastic intervention in time series data.
2022-11-29, Yiye Jiang, PhD student at Institut de Mathématiques de Bordeaux, France: Graph learning with autoregressive models for complex data types.
2022-11-21, Aude Sportisse, Postdoc at 3iA Côte d’Azur, France: Informative labels in Semi-Supervised Learning.
2022-11-16, Marco Carone, Associate Professor of Biostatistics at University of Washington, USA: Inference for algorithm-agnostic variable importance.
2022-11-02, Curtis Northcutt, CEO & Co-Founder of Cleanlab, USA: Cleanlab: Automatically Find and Fix Errors in ML Datasets.
2022-10-26, Ruishan Liu, Postdoc at Stanford, USA: AI for clinical trials design.
2022-10-18, Arthur Gretton, Professor at University College London, UK: Deep Causal Inference.
2022-10-14, Matthieu Marbac-Lourdelle, Assistant Professor at ENSAI/CREST, France: Model selection for non-parametric mixtures and hidden Markov models.
2022-09-27, Elizabeth Stuart, Professor at Johns Hopkins University, USA: Combining experimental and population data to estimate population treatment effects.
2022-09-14, Mary Beth Nebel, Assistant Professor of Neurology at Johns Hopkins University, USA: Accounting for motion in fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?
2022-07-06, Romain Pirracchio, Professor at University of California San Francisco, USA: Heterogeneous Treatment Effect in medicine: convergence between ML and Causal Inference.
2022-06-29, François Husson, Professor at Agrocampus Ouest, France: Visualisation de données multi-tableaux par analyse factorielle multiple.
2022-06-15, Alexandre Perez, PhD Student at SoDa team, Inria, France: Beyond calibration: estimating the grouping loss of modern neural networks.
2022-06-10, Eric Laber, Professor of Statistical Science at Duke University, USA: Safe Contextual Bandits in mHealth.
2022-06-07, Sofia Triantafyllou, Assistant Professor at University of Crete, Greece: Causal effect estimation using observational and experimental data.
2022-06-03, Michael Elliott, Professor of Biostatistics at the University of Michigan, USA: Using Synergies Between Survey Statistics and Causal Inference to Improve Transportability of Clinical Trials.
2022-05-30, Sylvain Sardy, Associate Professor at University of Geneva, Switzerland: A phase transition for finding needles in nonlinear haystacks with LASSO artificial neural networks.
2022-05-18, Chris Harschaw, Postdoctoral Scholar at Simons Institute, USA: Interference in Randomized Experiments: Survey and Challenges.
2022-05-16, Jeffrey Näf and Meta Lina Spohn, PhD students at ETH Zürich, Switzerland: Imputation Scores: How to choose an imputation method?
2022-05-11, Erica Moodie, Professor of Biostatistics at McGill University, Canada: Regression-Based Methods To Estimate Adaptive Treatment Strategies.
2022-04-27, Nathan Kallus, Assistant Professor at Cornell University and Cornell Tech, USA: Smooth Contextual Bandits.
2022-03-30, Felipe Tobar, Associate Professor at the Universidad de Chile, Chile: Gaussian processes, missing data, and optimal transport.
2022-03-14, Jiwei Zhao, Assistant Professor at the University of Wisconsin–Madison, USA: A Journey of Understanding Nonignorable Missingness and Some Reflections.
2022-02-16, Fredrik Johansson, Assistant Professor at Chalmers University of Technology, Sweden: Generalization Bounds for Estimation of Causal Effects.
2022-02-14, Celestine Mendler-Dünner, Research Group Lead at the Max Planck Institute for Intelligent Systems in Tübingen, Germany: Performative Prediction.
2022-01-26, Torsten Hothorn, Professor at the University of Zürich, Switzerland: Transformation Models: Pushing the Boundaries.
2022-01-17, Robin Genuer, Associate professor at ISPED, Université de Bordeaux, France: Fréchet random forests for metric space valued regression with non euclidean predictors.
2022-01-12, David Haziza, Professor at the University of Ottawa, Canada: Efficient multiply robust imputation in the presence of influential units in surveys.
2022-01-10, Ioanna Manolopoulou, Associate Professor at University College London, UK: Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation from randomized and observational data.
2022-01-05, Clément Bénard, Research Engineer in Machine Learning & Statistics at Safran, France: Variable importance for random forests: MDA and Shapley effects.
2021-12-13, Christos Thrampoulidis, Assistant Professor at the University of British Columbia in Vancouver, Canada: Blessings and Curses of Overparameterization: Insights from High-Dimensional Statistics.
2021-12-08, Irina Degtiar, Statistician at Mathematica Policy Research, USA: Generalizability and Transportability Methods for Estimating Causal Population Effects & Combining Randomized and Observational Data for Generalizability.
2021-12-03, reading group with Bénédicte Colnet.
2021-11-10, Alexandre Hippert-Ferrer, Postdoctoral researcher at Université Paris Nanterre, France: Robust low-rank covariance matrix estimation with missing values and application to classification problems.
2021-11-08, Irina Gaynanova, Associate Professor at Texas A&M University, USA: Data integration with mixed types of measurements.
2021-11-04, Margaux Zaffran, PhD student at INRIA: Adaptive Conformal Predictions for Time Series
2021-10-25, Malgorzata Bogdan, Professor at the University of Wroclaw, Poland: Recent developments on the Sorted L-One Penalized Estimator.
2021-10-18, Stephen Bates, Postdoctoral researcher at the University of California Berkeley, USA: Cross-validation: what does it estimate and how well does it do it?
2021-10-11, Alexandre Perez, PhD student at Inria, France.
2021-10-06, Samir Khan, PhD student at Stanford, USA: Adaptive normalization for IPW estimation
2021-10-04, Guillaume Staerman, PhD student at Télécom Paris, France: (Functional) Anomaly detection through using data depth.
2021-09-29, Andrew Jesson, PhD student at the University of Oxford, UK: Facing Uncertainty in Decision Making under Heterogeneous Effects.
2021-09-27, Damien Grasset, master student at IRT Montreal, Canada: Causal Reinforcement Learning using Observational and Interventional Data
2021-09-08, Wen Wei Loh, Postdoctoral Research Fellow at Ghent University, Belgium: Confounder selection strategies targeting stable treatment effect estimators.
2021-07-07, Giulio Grossi, PhD student at University of Florence, Italy.
2021-06-30, Élise Dumas, PhD student at RT2Lab and CBIO, Institut Curie, France: Analysing the impact of co-medications on Breast Cancer survival using data from the French social security system
2021-06-16, Juliette Chevallier, Postdoctoral researcher at Maasai, Inria Sophia-Antipolis, France.
2021-06-02, Pavlo Mozharovskyi, Associate Professor at Télécom Paris, France, Depth for curve data and applications
2021-05-28, Jonathan Berrisch, PhD student at University of Duisburg Essen, Germany.
2021-05-12, reading group with Marine Le Morvan.
2021-05-05, Yifan Cui, postoctoral research, University of Pennsylvania, USA: Treatment regime or survival forest.
2021-04-28, reading group with Bénédicte Colnet, MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA, Clément Bénard, Sébastien da Veiga, Erwan Scornet
2021-04-21, Yaniv Romano, Assistant professor at Technion, Israel Institute of Technology: Classification with Valid and Adaptive Coverage
2021-04-07, reading group with Margaux Zaffran, Conformalized Quantile Regression, Yaniv Romano, Evan Patterson, Emmnuel J. Candès
2021-03-31, Arnaud Gloaguen, Multiblock and multiway data analysis.
2021-03-24, reading group with Imke Mayer, Prediction, Estimation, and Attribution, Bradley Efron
2021-03-17, Allan Jérolon, Assistant professor at University of Paris, France: Causal mediation analysis in presence of multiple mediators uncausally related
2021-03-12, reading group with Costanza Tortù Ridge Regularizaton: an Essential Concept in Data Science, Trevor Hastie
2021-03-10, Maxime He, Data Scientist at Owkin, France: Yet another causality conceptualisation?
2021-03-03, Jiaxuan You, PhD student at Stanford University, USA: Handling Missing Data with Graph Representation Learning
2021-02-17, Ludovic Arnould, PhD student at Sorbonne University, LPSM, France: Tree-layer structure of Deep Forests
2021-02-03, Suzie Cro, Research Fellow at Imperial Clinical Trials Unit, UK: Controlled multiple imputation: an accessible flexible tool for sensitivity analysis of clinical trials with different types of missing data
2021-01-27, Margaux Brégère, Researcher at EDF R&D, Saclay: Stochastic Bandit Algorithms for Demand Side Management
2020-12-09, Nicole Erler, Postdoctoral researcher at Erasmus Medical Center, Rotterdam: Joint Analysis and Imputation of Incomplete Data in R: A Fully Bayesian Approach for Handling Missing Values in Complex Settings
2020-11-25, Carlos Cinelli, PhD student at University of California, USA: Generalizing Experimental Results by Leveraging Knowledge of Mechanisms
2020-11-18, Constantin Philipenko, PhD student at CMAP, École Polytechnique: Artemis: tight convergence guarantees for bidirectional compression in Federated Learning
2020-10-21, Yen-Chi Chen, Assistant Professor at University of Washington, USA: Pattern graphs: a graphical approach to nonmonotone missing data
2020-10-14, Bénédicte Colnet, PhD student at Parietal, Inria: Causal inference methods for combining randomizedtrials and observational studies: a review
2020-10-07, Qiming Du, Postdoctoral researcher at LPSM, Sorbonne Université: Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects
2020-10-01, Nathan Kallus, Assistant Professor at Cornell University and Cornell Tech, USA: Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond
2020-09-24, Issa Dahabreh, Associate Professor at Brown University, USA: Randomized trials and their observational emulations: a framework for benchmarking and joint analysis
2020-09-02, Quentin Bertrand, PhD student at Parietal, Inria: Implicit differentiation of Lasso-type models for hyperparameter optimization
2020-08-07, Alexandre Pérez, Master student at McGill University, Canada: Benchmark of methods to handle missing values in predictive models
2020-05-20, Razieh Nabi, Graduate Research Assistant at Johns Hopkins University, USA: Full Law Identification In Graphical Models Of Missing Data: Completeness Results
2020-05-14, Juha Karvanen, Professor of Statistics at University of Jyväskylä, Finland: Causal inference with multiple incomplete data sources
2020-02-04, Mathurin Massias, PhD student at Parietal, Inria: Optimizational and statistical contributions to the L21 -regularized M/EEG inverse problem
2019-12-03, Marine Le Morvan and Nicolas Prost, Postdoctoral reasarcher and PhD student, Parietal, Inria: Linear predictor on linearly-generated data with missing values: non consistency and solutions
2019-11-12, Consuelo Martínez Fontaine, PhD student at University Paris Saclay: A statistical Tephrochronology study of the Southern and Austral Volcanic Zones of the Andes.
2019-11-04, Bénédicte Colnet, Master student at University Pierre and Marie Curie: Bioinformatic screening of gut microbiome metabolic capacities
2019-10-16, Lucas Martin, PhD student, CMAP, Ecole Polytechnique: Causal inference and treatment estimation : An application to the UKBioBank dataset
2019-10-02, Arthur Mensch, Postdoctoral research at École Normale Supérieure, Paris Geometric losses for distributional learning
2019-09-16, Ramiro Camino, PhD at University of Luxembourg, Luxembourg: An overview of Tabular Data Imputation with Deep Generative Models
2019-09-03, Anqui Fu, PhD student at Stanford University, USA: Anderson Accelerated Douglas-Rachford Splitting
2019-05-22, Wei Jiang, PhD student at CMAP, Ecole Polytechnique: High-dimensional regression with noisy and missing data
2019-04-30, Imke Mayer, PhD student at EHESS, Paris: Doubly robust treatment effect estimation with incomplete confounders
2019-04-24, Teresa Alves De Sousa, Master student at CMAP, Ecole Polytechnique: Matching techniques in causal inference
2019-04-03, Pierre-Alexandre Mattei, Research scientist at Inria, Sophia Antipolis: Deep latent variable models: estimation and missing data imputation
2019-03-28, Quentin Paris, Assistant Professor, HSE University, Moscow, Russia: Estimation de barycentres dans les espaces métriques et applications
2019-03-06, Nicolas Prost, PhD student at CMAP, Ecole Polytechnique: On the consistency of supervised learning with missing values
2018-11-26, Imke Mayer, PhD student at EHESS, Paris: A Review on Causal Inference with Focus on Average Treatment Effect Estimation
2018-11-13, Wei Jiang, PhD student at CMAP, Ecole Polytechnique: Model selection with missing values – using Adaptive Bayesian SLOPE
2018-10-05, Aude Sportisse, PhD student at LPSM, Sorbonne Université: Low rank estimation with MNAR data
2018-09-17, Antoine Ogier, Master student at CMAP, Ecole Polytechnique: Cross-validation and imputation : handling missing data for hemorrhagic shock prediction
2018-09-12, Timothée Tabouy, PhD student at AgroParisTech: Variational inference for Stochastic Block Models from sampled data
2018-08-28, Fabien Laporte, Postdoctoral researcher at MODAL, Inria: Dealing with missing data in model-based clustering through a MNAR model
2018-07-19, Avarinth Chembu, Master student at CMAP, Ecole Polytechnique: Summary on fast SVD techniques and parallel computing
2018-06-29, Madeleine Udell, Assistant Professor at Cornell University, USA: Big data is low rank
2018-06-21, Félix Balazard, PhD data scientist at Owkin, LPSM and Inserm: Causality for personalized medicine
2018-06-12, Aude Sportisse, PhD student at LPSM, Sorbonne Université: Some methods for handling data generated by MNAR mechanisms
2018-06-05, Burim Ramosaj, PhD student at the Institute of Statistics, University of Ulm, Germany: Statistical inference using machine learning algorithms: the random forest model
2018-05-22, Hoi To Wai, Postdoctoral researcher, Arizona State University (ASU), USA: Using second-order information to accelerate incremental gradient methods
2018-05-07, Nicolas Prost, PhD student at CMAP, Ecole Polytechnique: Decision trees with missing values
2018-05-02, Pascaline Descloux, PhD student at University of Geneva, Swiss: Model selection with Lasso-Zero
2018-04-23, Wei Jiang: Stochastic approximation EM for logistic regression with missing values
Introduction to causal inference for statisticians
Targeted learning
We also organize common group meetings with Gaël Varoquaux’s Inria team. For more information about these group meetings, contact Bénédicte Colnet.
Members of our group follow different seminars and events, a selection is given in the google calendar. Additionally, we keep a list of conferences and summer schools that some of us potentially plan to attend here.