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Found 4 papers, 2 papers with code
Meta-Designing Quantum Experiments with Language Models
Artificial Intelligence (AI) has the potential to significantly advance scientific discovery by finding solutions beyond human capabilities.
Insights into Pre-training via Simpler Synthetic Tasks
Second, to our surprise, we find that pre-training on a simple and generic synthetic task defined by the Set function achieves $65\%$ of the benefits, almost matching LIME.
On-Policy Robot Imitation Learning from a Converging Supervisor
Existing on-policy imitation learning algorithms, such as DAgger, assume access to a fixed supervisor.
Safety Augmented Value Estimation from Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks
Reinforcement learning (RL) for robotics is challenging due to the difficulty in hand-engineering a dense cost function, which can lead to unintended behavior, and dynamical uncertainty, which makes exploration and constraint satisfaction challenging.
Model-based Reinforcement Learning
reinforcement-learning
+1
