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Found 2 papers, 1 papers with code
Introducing Milabench: Benchmarking Accelerators for AI
AI workloads, particularly those driven by deep learning, are introducing novel usage patterns to high-performance computing (HPC) systems that are not comprehensively captured by standard HPC benchmarks.
CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning
In this work, we take an alternative approach and propose CtRL-Sim, a method that leverages return-conditioned offline reinforcement learning (RL) to efficiently generate reactive and controllable traffic agents.
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