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Encoders and Ensembles for Task-Free Continual Learning
We present an architecture that is effective for continual learning in a...
05/27/2021 ∙ by Murray Shanahan, et al. ∙
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Representation Learning via Invariant Causal Mechanisms
Self-supervised learning has emerged as a strategy to reduce the relianc...
10/15/2020 ∙ by Jovana Mitrovic, et al. ∙
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Amortized learning of neural causal representations
Causal models can compactly and efficiently encode the data-generating p...
08/21/2020 ∙ by Nan Rosemary Ke, et al. ∙
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Causally Correct Partial Models for Reinforcement Learning
In reinforcement learning, we can learn a model of future observations a...
02/07/2020 ∙ by Danilo J. Rezende, et al. ∙
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Causal Reasoning from Meta-reinforcement Learning
Discovering and exploiting the causal structure in the environment is a ...
01/23/2019 ∙ by Ishita Dasgupta, et al. ∙
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Causal Inference via Kernel Deviance Measures
Discovering the causal structure among a set of variables is a fundament...
04/12/2018 ∙ by Jovana Mitrovic, et al. ∙
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Hierarchical Adversarially Learned Inference
We propose a novel hierarchical generative model with a simple Markovian...
02/04/2018 ∙ by Mohamed Ishmael Belghazi, et al. ∙
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DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression
Performing exact posterior inference in complex generative models is oft...
02/15/2016 ∙ by Jovana Mitrovic, et al. ∙
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