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10/01/2022
DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability
In representation learning, a common approach is to seek representations...
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07/22/2022
Discrete Key-Value Bottleneck
Deep neural networks perform well on prediction and classification tasks...
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01/31/2022
Compositional Multi-Object Reinforcement Learning with Linear Relation Networks
Although reinforcement learning has seen remarkable progress over the la...
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10/07/2021
Boxhead: A Dataset for Learning Hierarchical Representations
Disentanglement is hypothesized to be beneficial towards a number of dow...
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07/17/2021
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain
An important component for generalization in machine learning is to unco...
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07/12/2021
Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning
Learning data representations that are useful for various downstream tas...
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07/02/2021
Backward-Compatible Prediction Updates: A Probabilistic Approach
When machine learning systems meet real world applications, accuracy is ...
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10/27/2020
On the Transfer of Disentangled Representations in Realistic Settings
Learning meaningful representations that disentangle the underlying stru...
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10/08/2020
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
Despite recent successes of reinforcement learning (RL), it remains a ch...
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06/14/2020