Accepted Papers

• Latent Stochastic Interpolants for Probabilistic Time Series Forecasting

  Bourgeat, M. & Surendran, S.

  ICML 2026 Workshop 2026
  Paper

• Latent Guided Sampling for Combinatorial Optimization

  Surendran, S., Fermanian, A., & Le Corff, S.

  ICML 2026 2026
  Paper Code Poster

• Diffusion-Driven Latent Guided Sampling for Neural Combinatorial Optimization

  Surendran, S., Fermanian, A., & Le Corff, S.

  ICLR 2026 Workshop 2026
  Paper Code

• Wasserstein Convergence of Critically Damped Langevin Diffusions

  Strasman, S., Surendran, S., Boyer, C., Le Corff, S., Lemaire, V., & Ocello, A.

  NeurIPS 2025 2025
  Paper Code Poster

• Theoretical Convergence Guarantees for Variational Autoencoders

  Surendran, S., Godichon-Baggioni, A., & Le Corff, S.

  AISTATS 2025 2025
  Paper Code Poster

• Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation

  Surendran, S., Godichon-Baggioni, A., Fermanian, A., & Le Corff, S.

  NeurIPS 2024 2024
  Paper Code Poster

• A Penalized Criterion for Selecting the Number of Clusters for K-medians

  Godichon-Baggioni, A. & Surendran, S.

  JCGS 2024 2024
  Paper Code

Preprints

• Non-asymptotic Convergence of Stochastic Gradient Descent in Score-based Generative Models

  Strasman, S., Surendran, S., & Le Corff, S.

  Preprint 2026
  Paper

• Convergence of Multi-Level Markov Chain Monte Carlo Adaptive Stochastic Gradient Algorithms

  Godichon-Baggioni, A., Lang, G., Le Corff, S., Stoehr, J. & Surendran, S.

  Preprint 2026
  Paper