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11/18/2022
Exploring through Random Curiosity with General Value Functions
Efficient exploration in reinforcement learning is a challenging problem...
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03/25/2022
Unsupervised Learning of Temporal Abstractions with Slot-based Transformers
The discovery of reusable sub-routines simplifies decision-making and pl...
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12/09/2020
On the Binding Problem in Artificial Neural Networks
Contemporary neural networks still fall short of human-level generalizat...
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11/25/2020
Unsupervised Object Keypoint Learning using Local Spatial Predictability
We propose PermaKey, a novel approach to representation learning based o...
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10/07/2020
Hierarchical Relational Inference
Common-sense physical reasoning in the real world requires learning abou...
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10/05/2020
Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks
Neural networks (NNs) whose subnetworks implement reusable functions are...
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10/09/2019
Improving Generalization in Meta Reinforcement Learning using Learned Objectives
Biological evolution has distilled the experiences of many learners into...
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06/03/2019
A Perspective on Objects and Systematic Generalization in Model-Based RL
In order to meet the diverse challenges in solving many real-world probl...
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05/29/2019
Are Disentangled Representations Helpful for Abstract Visual Reasoning?
A disentangled representation encodes information about the salient fact...
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12/03/2018
Towards Accurate Generative Models of Video: A New Metric & Challenges
Recent advances in deep generative models have lead to remarkable progre...
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10/17/2018
A Case for Object Compositionality in Deep Generative Models of Images
Deep generative models seek to recover the process with which the observ...
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02/28/2018
Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions
Common-sense physical reasoning is an essential ingredient for any intel...
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08/11/2017
