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11/25/2022
Solving math word problems with process- and outcome-based feedback
Recent work has shown that asking language models to generate reasoning ...
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05/19/2022
Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning
Large language models (LLMs) have been shown to be capable of impressive...
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03/17/2022
Symmetry-Based Representations for Artificial and Biological General Intelligence
Biological intelligence is remarkable in its ability to produce complex ...
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11/10/2021
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision
A recently proposed class of models attempts to learn latent dynamics fr...
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11/09/2021
Which priors matter? Benchmarking models for learning latent dynamics
Learning dynamics is at the heart of many important applications of mach...
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11/03/2020
Representation Matters: Improving Perception and Exploration for Robotics
Projecting high-dimensional environment observations into lower-dimensio...
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10/28/2020
Representation learning for improved interpretability and classification accuracy of clinical factors from EEG
Despite extensive standardization, diagnostic interviews for mental heal...
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06/23/2020
Disentangling by Subspace Diffusion
We present a novel nonparametric algorithm for symmetry-based disentangl...
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09/30/2019
Hamiltonian Generative Networks
The Hamiltonian formalism plays a central role in classical and quantum ...
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09/30/2019
Equivariant Hamiltonian Flows
This paper introduces equivariant hamiltonian flows, a method for learni...
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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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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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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
