Thomas Miconi

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Enabling Continual Learning with Differentiable Hebbian Plasticity

Continual learning is the problem of sequentially learning new tasks or ...
06/30/2020 ∙ by Vithursan Thangarasa, et al. ∙ 0 ∙ share

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Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity

The impressive lifelong learning in animal brains is primarily enabled b...
02/24/2020 ∙ by Thomas Miconi, et al. ∙ 25 ∙ share

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Learning to Continually Learn

Continual lifelong learning requires an agent or model to learn many seq...
02/21/2020 ∙ by Shawn Beaulieu, et al. ∙ 43 ∙ share

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Estimating Q(s,s') with Deep Deterministic Dynamics Gradients

In this paper, we introduce a novel form of value function, Q(s, s'), th...
02/21/2020 ∙ by Ashley D. Edwards, et al. ∙ 7 ∙ share

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First-Order Preconditioning via Hypergradient Descent

Standard gradient descent methods are susceptible to a range of issues t...
10/18/2019 ∙ by Ted Moskovitz, et al. ∙ 22 ∙ share

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Differentiable plasticity: training plastic neural networks with backpropagation

How can we build agents that keep learning from experience, quickly and ...
04/06/2018 ∙ by Thomas Miconi, et al. ∙ 0 ∙ share

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The impossibility of "fairness": a generalized impossibility result for decisions

Various measures can be used to estimate bias or unfairness in a predict...
07/05/2017 ∙ by Thomas Miconi, et al. ∙ 0 ∙ share

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Learning to learn with backpropagation of Hebbian plasticity

Hebbian plasticity is a powerful principle that allows biological brains...
09/08/2016 ∙ by Thomas Miconi, et al. ∙ 0 ∙ share

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Neural networks with differentiable structure

While gradient descent has proven highly successful in learning connecti...
06/20/2016 ∙ by Thomas Miconi, et al. ∙ 0 ∙ share

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Thomas Miconi

Featured Co-authors

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Rosanne Liu

Charles Isbell

Aditya Rawal

Ashley D. Edwards

Enabling Continual Learning with Differentiable Hebbian Plasticity

Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity

Learning to Continually Learn

Estimating Q(s,s') with Deep Deterministic Dynamics Gradients

First-Order Preconditioning via Hypergradient Descent

Differentiable plasticity: training plastic neural networks with backpropagation

The impossibility of "fairness": a generalized impossibility result for decisions

Learning to learn with backpropagation of Hebbian plasticity

Neural networks with differentiable structure