TensorFlow

Mode-Constrained Exploration for Model-Based Reinforcement Learning

This work presents a learning-based control method for navigating to a target state in unknown, or partially unknown, multimodal dynamical systems. In particular, it develops a …

Aidan Scannell

• 24 Sep, 2022 • 1 min read

Machine-Learning

PhD Thesis: Bayesian Learning for Control in Multimodal Dynamical Systems

Mode remaining navigation (and exploration) in unknown multimodal dynamical systems via model-based reinforcement learning.

Aidan Scannell

• 24 Sep, 2022 • 1 min read

Gaussian-Processes

Identifiable Mixtures of Sparse Variational Gaussian Process Experts

Aidan Scannell

• 26 May, 2021 • 1 min read

Gaussian-Processes

Identifiable Mixtures of Sparse Variational Gaussian Process Experts

This work introduces a variational lower bound for the Mixture of Gaussian Process Experts model with a GP-based gating network based on sparse GPs. The model (and inference) are …

Aidan Scannell

• 16 Nov, 2020 • 1 min read