We have 2 of 4 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
This work examines both model behavior and internal representations, using the empirical neural tangent kernel (NTK) as the primary diagnostic tool, and develops practical guidance for designing DR schemes, selecting models, and detecting shortcut learning.
Deep reinforcement learning (DRL) has achieved great success in many simulated and real-world robotic tasks. However, the difficulty of designing efficient and dense reward functions makes applying DRL to tackle complex long-horizon and open-world tasks a great challenge. Generative adversarial imitation learning (GAIL...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
