I'll be giving a lecture on model-based RL at the Cambridge Ellis Unit Summer School on Probabilistic Machine Learning 2024.
Sequential learning paradigms pose challenges for gradient-based deep learning due to difficulties incorporating new data and retaining prior knowledge. While Gaussian processes …
I will be presenting our research on bayesian deep learning for sequential learning at the [International Workshop of Intelligent Autonomous Learning Systems …
We present a model-based RL algorithm that constrains training to a single dynamic mode with high probability. This is a difficult problem because the mode constraint is a hidden …
This project seeks to evaluate and compare different approaches for learning dynamics models in model-based RL. In particular, we plan to compare different approximate inference …