51 citations · 167 across the 27 of their papers we have counts for
4 papers · 2 filters
Towards Tractable Optimism in Model-Based Reinforcement Learning
Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder +2
The principle of optimism in the face of uncertainty is prevalent throughout sequential decision making problems such as multi-armed bandits and reinforcement learning (RL). To be…
Variational Integrator Graph Networks for Learning Energy Conserving Dynamical Systems
Shaan Desai, Marios Mattheakis, Stephen Roberts
Recent advances show that neural networks embedded with physics-informed priors significantly outperform vanilla neural networks in learning and predicting the long term dynamics o…
Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks
Bernardo Pérez Orozco, Stephen J Roberts
Recurrent neural networks (RNNs) are state-of-the-art in several sequential learning tasks, but they often require considerable amounts of data to generalise well. For many time se…
Learning Bijective Feature Maps for Linear ICA
Alexander Camuto, Matthew Willetts, Brooks Paige +2
Separating high-dimensional data like images into independent latent factors, i.e independent component analysis (ICA), remains an open research problem. As we show, existing proba…