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07/23/2021
Constellation: Learning relational abstractions over objects for compositional imagination
Learning structured representations of visual scenes is currently a majo...
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06/07/2021
SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition
To help agents reason about scenes in terms of their building blocks, we...
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02/04/2021
Alchemy: A structured task distribution for meta-reinforcement learning
There has been rapidly growing interest in meta-learning as a method for...
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07/17/2020
AlignNet: Unsupervised Entity Alignment
Recently developed deep learning models are able to learn to segment sce...
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05/29/2019
A Heuristic for Unsupervised Model Selection for Variational Disentangled Representation Learning
Disentangled representations have recently been shown to improve data ef...
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05/22/2019
COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration
Data efficiency and robustness to task-irrelevant perturbations are long...
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03/01/2019
Multi-Object Representation Learning with Iterative Variational Inference
Human perception is structured around objects which form the basis for o...
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01/22/2019
MONet: Unsupervised Scene Decomposition and Representation
The ability to decompose scenes in terms of abstract building blocks is ...
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01/21/2019
Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs
We present a simple neural rendering architecture that helps variational...
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12/05/2018
Towards a Definition of Disentangled Representations
How can intelligent agents solve a diverse set of tasks in a data-effici...
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08/20/2018
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies
Intelligent behaviour in the real-world requires the ability to acquire ...
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04/10/2018
Understanding disentangling in β-VAE
We present new intuitions and theoretical assessments of the emergence o...
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07/26/2017
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
Domain adaptation is an important open problem in deep reinforcement lea...
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07/11/2017
SCAN: Learning Abstract Hierarchical Compositional Visual Concepts
The natural world is infinitely diverse, yet this diversity arises from ...
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06/17/2016
