4 papers
Amortized Equation Discovery in Hybrid Dynamical Systems
Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas +1
Hybrid dynamical systems are prevalent in science and engineering to express complex systems with continuous and discrete states. To learn the laws of systems, all previous methods…
Towards the Reusability and Compositionality of Causal Representations
Davide Talon, Phillip Lippe, Stuart James +2
Causal Representation Learning (CRL) aims at identifying high-level causal factors and their relationships from high-dimensional observations, e.g., images. While most CRL works fo…
Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning
Fan Feng, Sara Magliacane
In many reinforcement learning tasks, the agent has to learn to interact with many objects of different types and generalize to unseen combinations and numbers of objects. Often a…
Graph Switching Dynamical Systems
Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas +1
Dynamical systems with complex behaviours, e.g. immune system cells interacting with a pathogen, are commonly modelled by splitting the behaviour into different regimes, or modes,…