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06/30/2023
Quantum State Assignment Flows
This paper introduces assignment flows for density matrices as state spa...
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10/01/2021
Powerpropagation: A sparsity inducing weight reparameterisation
The training of sparse neural networks is becoming an increasingly impor...
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10/27/2020
Behavior Priors for Efficient Reinforcement Learning
As we deploy reinforcement learning agents to solve increasingly challen...
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05/03/2019
Information asymmetry in KL-regularized RL
Many real world tasks exhibit rich structure that is repeated across dif...
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03/28/2019
Meta-Learning surrogate models for sequential decision making
Meta-learning methods leverage past experience to learn data-driven indu...
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01/31/2019
Functional Regularisation for Continual Learning using Gaussian Processes
We introduce a novel approach for supervised continual learning based on...
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01/17/2019
Attentive Neural Processes
Neural Processes (NPs) (Garnelo et al 2018a;b) approach regression by le...
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11/28/2018
Experience Replay for Continual Learning
Continual learning is the problem of learning new tasks or knowledge whi...
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07/04/2018
Neural Processes
A neural network (NN) is a parameterised function that can be tuned via ...
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05/16/2018
Progress & Compress: A scalable framework for continual learning
We introduce a conceptually simple and scalable framework for continual ...
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12/19/2017
