Michael Mathieu | DeepAI

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∙ 08/07/2023

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning

StarCraft II is one of the most challenging simulated reinforcement lear...

0 Michael Mathieu, et al. ∙

∙ 07/27/2021

Open-Ended Learning Leads to Generally Capable Agents

In this work we create agents that can perform well beyond a single, ind...

2 Open-Ended Learning Team, et al. ∙

∙ 11/10/2016

Disentangling factors of variation in deep representations using adversarial training

We introduce a conditional generative model for learning to disentangle ...

0 Michael Mathieu, et al. ∙

∙ 09/11/2016

Energy-based Generative Adversarial Network

We introduce the "Energy-based Generative Adversarial Network" model (EB...

0 Junbo Zhao, et al. ∙

∙ 11/17/2015

Deep multi-scale video prediction beyond mean square error

Learning to predict future images from a video sequence involves the con...

0 Michael Mathieu, et al. ∙

∙ 06/09/2015

Learning to Linearize Under Uncertainty

Training deep feature hierarchies to solve supervised learning tasks has...

0 Ross Goroshin, et al. ∙

∙ 06/08/2015

Stacked What-Where Auto-encoders

We present a novel architecture, the "stacked what-where auto-encoders" ...

0 Junbo Zhao, et al. ∙

∙ 12/24/2014

Learning Longer Memory in Recurrent Neural Networks

Recurrent neural network is a powerful model that learns temporal patter...

0 Tomas Mikolov, et al. ∙

∙ 12/24/2014

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

We examine the performance profile of Convolutional Neural Network train...

0 Nicolas Vasilache, et al. ∙

∙ 12/20/2014

Video (language) modeling: a baseline for generative models of natural videos

We propose a strong baseline model for unsupervised feature learning usi...

0 MarcAurelio Ranzato, et al. ∙

∙ 11/30/2014

The Loss Surfaces of Multilayer Networks

We study the connection between the highly non-convex loss function of a...

0 Anna Choromanska, et al. ∙

∙ 04/29/2014

Fast Approximation of Rotations and Hessians matrices

A new method to represent and approximate rotation matrices is introduce...

0 Michael Mathieu, et al. ∙

∙ 12/21/2013

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks

We present an integrated framework for using Convolutional Networks for ...

0 Pierre Sermanet, et al. ∙

∙ 12/20/2013

Fast Training of Convolutional Networks through FFTs

Convolutional networks are one of the most widely employed architectures...

0 Michael Mathieu, et al. ∙

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