Search Results for author:
Found 5 papers, 1 papers with code
Free Energy Risk Metrics for Systemically Safe AI: Gatekeeping Multi-Agent Study
We investigate the Free Energy Principle as a foundation for measuring risk in agentic and multi-agent systems.
Realistically distributing object placements in synthetic training data improves the performance of vision-based object detection models
When training object detection models on synthetic data, it is important to make the distribution of synthetic data as close as possible to the distribution of real data.
Video Killed the HD-Map: Predicting Multi-Agent Behavior Directly From Aerial Images
The development of algorithms that learn multi-agent behavioral models using human demonstrations has led to increasingly realistic simulations in the field of autonomous driving.
Conditional Permutation Invariant Flows
We present a novel, conditional generative probabilistic model of set-valued data with a tractable log density.
Critic Sequential Monte Carlo
We introduce CriticSMC, a new algorithm for planning as inference built from a composition of sequential Monte Carlo with learned Soft-Q function heuristic factors.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
