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07/18/2023
Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning
In many reinforcement learning tasks, the agent has to learn to interact...
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06/16/2023
BISCUIT: Causal Representation Learning from Binary Interactions
Identifying the causal variables of an environment and how to intervene ...
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06/01/2023
Graph Switching Dynamical Systems
Dynamical systems with complex behaviours, e.g. immune system cells inte...
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02/26/2023
Invariant Neural Ordinary Differential Equations
Latent neural ordinary differential equations have been proven useful fo...
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06/13/2022
iCITRIS: Causal Representation Learning for Instantaneous Temporal Effects
Causal representation learning is the task of identifying the underlying...
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03/30/2022
Factored Adaptation for Non-Stationary Reinforcement Learning
Dealing with non-stationarity in environments (i.e., transition dynamics...
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02/07/2022
CITRIS: Causal Identifiability from Temporal Intervened Sequences
Understanding the latent causal factors of a dynamical system from visua...
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07/06/2021
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning
Most approaches in reinforcement learning (RL) are data-hungry and speci...
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11/01/2020
Active Structure Learning of Causal DAGs via Directed Clique Tree
A growing body of work has begun to study intervention design for effici...
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07/02/2020
Verifiably Safe Exploration for End-to-End Reinforcement Learning
Deploying deep reinforcement learning in safety-critical settings requir...
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10/18/2018
An Upper Bound for Random Measurement Error in Causal Discovery
Causal discovery algorithms infer causal relations from data based on se...
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07/20/2017
Causal Transfer Learning
An important goal in both transfer learning and causal inference is to m...
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11/30/2016
Joint Causal Inference from Observational and Experimental Datasets
We introduce Joint Causal Inference (JCI), a powerful formulation of cau...
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06/22/2016
