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07/29/2021
Learning more skills through optimistic exploration
Unsupervised skill learning objectives (Gregor et al., 2016, Eysenbach e...
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12/14/2020
Relative Variational Intrinsic Control
In the absence of external rewards, agents can still learn useful behavi...
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01/22/2020
Q-Learning in enormous action spaces via amortized approximate maximization
Applying Q-learning to high-dimensional or continuous action spaces can ...
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06/12/2019
Fast Task Inference with Variational Intrinsic Successor Features
It has been established that diverse behaviors spanning the controllable...
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11/28/2018
Unsupervised Control Through Non-Parametric Discriminative Rewards
Learning to control an environment without hand-crafted rewards or exper...
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06/15/2017
Variational Approaches for Auto-Encoding Generative Adversarial Networks
Auto-encoding generative adversarial networks (GANs) combine the standar...
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05/09/2016
Theano: A Python framework for fast computation of mathematical expressions
Theano is a Python library that allows to define, optimize, and evaluate...
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06/01/2015
Blocks and Fuel: Frameworks for deep learning
We introduce two Python frameworks to train neural networks on large dat...
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05/13/2015
Brain Tumor Segmentation with Deep Neural Networks
In this paper, we present a fully automatic brain tumor segmentation met...
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03/05/2015
EmoNets: Multimodal deep learning approaches for emotion recognition in video
The task of the emotion recognition in the wild (EmotiW) Challenge is to...
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12/20/2014
Self-informed neural network structure learning
We study the problem of large scale, multi-label visual recognition with...
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06/10/2014
Generative Adversarial Networks
We propose a new framework for estimating generative models via an adver...
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12/21/2013
An empirical analysis of dropout in piecewise linear networks
The recently introduced dropout training criterion for neural networks h...
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08/20/2013
Pylearn2: a machine learning research library
Pylearn2 is a machine learning research library. This does not just mean...
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02/18/2013
Maxout Networks
We consider the problem of designing models to leverage a recently intro...
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11/23/2012
