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05/18/2023
Brain-inspired learning in artificial neural networks: a review
Artificial neural networks (ANNs) have emerged as an essential tool in m...
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02/11/2023
A large parametrized space of meta-reinforcement learning tasks
We describe a parametrized space for simple meta-reinforcement-learning ...
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12/16/2021
Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learning
In meta-learning, networks are trained with external algorithms to learn...
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07/04/2021
Multi-layer Hebbian networks with modern deep learning frameworks
Deep learning networks generally use non-biological learning methods. By...
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06/30/2020
Enabling Continual Learning with Differentiable Hebbian Plasticity
Continual learning is the problem of sequentially learning new tasks or ...
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02/24/2020
Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity
The impressive lifelong learning in animal brains is primarily enabled b...
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02/21/2020
Learning to Continually Learn
Continual lifelong learning requires an agent or model to learn many seq...
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02/21/2020
Estimating Q(s,s') with Deep Deterministic Dynamics Gradients
In this paper, we introduce a novel form of value function, Q(s, s'), th...
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10/18/2019
First-Order Preconditioning via Hypergradient Descent
Standard gradient descent methods are susceptible to a range of issues t...
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04/06/2018
Differentiable plasticity: training plastic neural networks with backpropagation
How can we build agents that keep learning from experience, quickly and ...
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07/05/2017
The impossibility of "fairness": a generalized impossibility result for decisions
Various measures can be used to estimate bias or unfairness in a predict...
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09/08/2016
Learning to learn with backpropagation of Hebbian plasticity
Hebbian plasticity is a powerful principle that allows biological brains...
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06/20/2016
