3 papers
cs.CV2026
Test-Time Conditioning with Representation-Aligned Visual Features
Nicolas Sereyjol-Garros, Ellington Kirby, Victor Letzelter +2
While representation alignment with self-supervised models has been shown to improve diffusion model training, its potential for enhancing inference-time conditioning remains large…
cs.LG2025
Winner-takes-all for Multivariate Probabilistic Time Series Forecasting
Adrien Cortés, Rémi Rehm, Victor Letzelter
We introduce TimeMCL, a method leveraging the Multiple Choice Learning (MCL) paradigm to forecast multiple plausible time series futures. Our approach employs a neural network with…
cs.RO2024
Annealed Winner-Takes-All for Motion Forecasting
Yihong Xu, Victor Letzelter, Mickaël Chen +2
In autonomous driving, motion prediction aims at forecasting the future trajectories of nearby agents, helping the ego vehicle to anticipate behaviors and drive safely. A key chall…