5 citations · 16 across the 15 of their papers we have counts for
3 papers · 1 filter
Getting By Goal Misgeneralization With a Little Help From a Mentor
Tu Trinh, Mohamad H. Danesh, Nguyen X. Khanh +1
While reinforcement learning (RL) agents often perform well during training, they can struggle with distribution shift in real-world deployments. One particularly severe risk of di…
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning
Shengyi Huang, Quentin Gallouédec, Florian Felten +30
In many Reinforcement Learning (RL) papers, learning curves are useful indicators to measure the effectiveness of RL algorithms. However, the complete raw data of the learning curv…
Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower Resolutions
Saeed Khorram, Mingqi Jiang, Mohamad Shahbazi +2
Despite extensive research on training generative adversarial networks (GANs) with limited training data, learning to generate images from long-tailed training distributions remain…