Karol Kurach | DeepAI

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∙ 07/25/2019

Google Research Football: A Novel Reinforcement Learning Environment

Recent progress in the field of reinforcement learning has been accelera...

16 Karol Kurach, et al. ∙

∙ 12/03/2018

Towards Accurate Generative Models of Video: A New Metric & Challenges

Recent advances in deep generative models have lead to remarkable progre...

0 Thomas Unterthiner, et al. ∙

∙ 10/17/2018

A Case for Object Compositionality in Deep Generative Models of Images

Deep generative models seek to recover the process with which the observ...

0 Sjoerd van Steenkiste, et al. ∙

∙ 07/12/2018

The GAN Landscape: Losses, Architectures, Regularization, and Normalization

Generative Adversarial Networks (GANs) are a class of deep generative mo...

6 Karol Kurach, et al. ∙

∙ 03/29/2018

MemGEN: Memory is All You Need

We propose a new learning paradigm called Deep Memory. It has the potent...

0 Sylvain Gelly, et al. ∙

∙ 11/28/2017

Are GANs Created Equal? A Large-Scale Study

Generative adversarial networks (GAN) are a powerful subclass of generat...

0 Mario Lucic, et al. ∙

∙ 05/23/2017

Better Text Understanding Through Image-To-Text Transfer

Generic text embeddings are successfully used in a variety of tasks. How...

0 Karol Kurach, et al. ∙

∙ 06/15/2016

Smart Reply: Automated Response Suggestion for Email

In this paper we propose and investigate a novel end-to-end method for a...

0 Anjuli Kannan, et al. ∙

∙ 11/21/2015

Adding Gradient Noise Improves Learning for Very Deep Networks

Deep feedforward and recurrent networks have achieved impressive results...

0 Arvind Neelakantan, et al. ∙

∙ 11/19/2015

Neural Random-Access Machines

In this paper, we propose and investigate a new neural network architect...

0 Karol Kurach, et al. ∙

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