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07/14/2023
Linking vision and motion for self-supervised object-centric perception
Object-centric representations enable autonomous driving algorithms to r...
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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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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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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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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
