activity
20242026
collaborators

6 papers

cs.CL2026

Learning to Evict from Key-Value Cache

Luca Moschella, Laura Manduchi, Ozan Sener

The growing size of Large Language Models (LLMs) makes efficient inference challenging, primarily due to the memory demands of the autoregressive Key-Value (KV) cache. Existing evi…

stat.ML2025

Addressing Misspecification in Simulation-based Inference through Data-driven Calibration

Antoine Wehenkel, Juan L. Gamella, Ozan Sener +4

Driven by steady progress in deep generative modeling, simulation-based inference (SBI) has emerged as the workhorse for inferring the parameters of stochastic simulators. However,…

cs.LG2025

Robust Autonomy Emerges from Self-Play

Marco Cusumano-Towner, David Hafner, Alex Hertzberg +9

Self-play has powered breakthroughs in two-player and multi-player games. Here we show that self-play is a surprisingly effective strategy in another domain. We show that robust an…

stat.ML2024

Simulation-based Inference for Cardiovascular Models

Antoine Wehenkel, Laura Manduchi, Jens Behrmann +6

Over the past decades, hemodynamics simulators have steadily evolved and have become tools of choice for studying cardiovascular systems in-silico. While such tools are routinely u…

cs.LG2024

Leveraging Cardiovascular Simulations for In-Vivo Prediction of Cardiac Biomarkers

Laura Manduchi, Antoine Wehenkel, Jens Behrmann +6

Whole-body hemodynamics simulators, which model blood flow and pressure waveforms as functions of physiological parameters, are now essential tools for studying cardiovascular syst…

cs.CV2024

Random Representations Outperform Online Continually Learned Representations

Ameya Prabhu, Shiven Sinha, Ponnurangam Kumaraguru +3

Continual learning has primarily focused on the issue of catastrophic forgetting and the associated stability-plasticity tradeoffs. However, little attention has been paid to the e…