
Disentangling by Subspace Diffusion
We present a novel nonparametric algorithm for symmetrybased disentangl...
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AbInitio Solution of the ManyElectron Schrödinger Equation with Deep Neural Networks
Given access to accurate solutions of the manyelectron Schrödinger equa...
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Towards a Definition of Disentangled Representations
How can intelligent agents solve a diverse set of tasks in a dataeffici...
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Spectral Inference Networks: Unifying Spectral Methods With Deep Learning
We present Spectral Inference Networks, a framework for learning eigenfu...
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Unrolled Generative Adversarial Networks
We introduce a method to stabilize Generative Adversarial Networks (GANs...
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Connecting Generative Adversarial Networks and ActorCritic Methods
Both generative adversarial networks (GAN) in unsupervised learning and ...
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Learning to learn by gradient descent by gradient descent
The move from handdesigned features to learned features in machine lear...
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Convolution by Evolution: Differentiable Pattern Producing Networks
In this work we introduce a differentiable version of the Compositional ...
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David Pfau
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