Program > Posters

Chazal Clémentine

A computable Measure of Suboptimality for Entropy-Regularised Variational Objectives

Attwood Lucy

A Normalised Kernel Test for Independence

Bringas Miranda Juliet

A Novel Approach to Distributional Reinforcement Learning via Moment Matching

Legacci Davide

Adapting to Conflict: Equilibrium Structure and Adaptive Learning in Harmonic Games

Zhou Julien

Beyond Expectations: Best-of-Both-Worlds Guarantees with High Probability for Multi-Armed Bandits

Cernocky Tomas

Computational design of symmetric proteins

Diemert Eustache

Contextualizing Pan-Tropical Allometric Models for Biomass Estimation

Guilmeau Thomas

Convergence of projected stochastic natural gradient variational inference for various step size and sample or batch size schedules

Giard Romane

Convex estimation of Gaussian Mixture Models with unknown diagonal covariances

Lizé Louise

Crustal fracture classification and parameter estimation from InSAR displacement fields with interpretable descriptors

Rossini Orlane

Deep Reinforcement Learning for Bayes-Adaptive Impulse Control of PDMPs

Lu Haiyang

Differentially Private Reinforcement Learning using Randomized Value Functions

Dyssel Lucas

Difficulty-Aware Continual Learning for Segmentation with Researcher-in-the-Loop

Cruz Cabezas Luben Miguel

Epistemic Uncertainty in Conformal Scores: A Unified Approach

Hernandez Louis

Foundation Causal Structure Model (FCSM): Source-Agnostic DAG-Constrained Causal Graph Learning

Afantenos Stergos

FrameNet Semantic Role Classification by Analogy

Konig Caroline

From Trees to Phenotypes: Random Forest Leaf Clustering for Patient Subgroup Discovery

Trezza Giovanni

Full Equivariance in Score-Based Generative Models Toward Molecules and Materials Inverse Design

Flamand Kessang

Functional Central Limit Theorem for Stochastic Gradient Descent

Jannin Louis

Gaussian models for improved short-term congestion forecasting of power grids

Niang Seydina Ousmane

Importance weighting variational graph autoencoder for nodes clustering of complex networks

Ndiaye Aminata

Learning Counterfactual Densities via Marginal Contrastive Discrimination

Bordoy Tomás

Multi-Scale Context Fusion for Cancer Segmentation in Whole Slide Images

Adamo Davide

Neural approximation of Procrustes-Wasserstein transport maps

Emonet Rémi

On the Closed-Form of Flow Matching: Generalization Does Not Arise from Target Stochasticity

Alamichel Louise

Partially exchangeable enriched stochastic block models

Leite Alessandro

Partition Trees: Conditional Density Estimation over General Outcome Spaces

Pujol Romain

Reinforcement Learning for the Dynamic VRPTW

Forbes Florence

Scalable Bayesian Experimental Design with diffusions

Leclerc Sarah

Suivi de lignées cellulaires HEK293 combinant imagerie holographique et apprentissage automatique