activity
20112019
most citedDRAW: A Recurrent Neural Network For Image Generation

963 citations · 1.3k across the 5 of their papers we have counts for

collaborators

9 papers

cs.LG201916 cited

Shaping Belief States with Generative Environment Models for RL

Karol Gregor, Danilo Jimenez Rezende, Frederic Besse +3

When agents interact with a complex environment, they must form and maintain beliefs about the relevant aspects of that environment. We propose a way to efficiently train expressiv…

cs.CV2016

What is the Best Feature Learning Procedure in Hierarchical Recognition Architectures?

Kevin Jarrett, Koray Kvukcuoglu, Karol Gregor +1

(This paper was written in November 2011 and never published. It is posted on arXiv.org in its original form in June 2016). Many recent object recognition systems have proposed usi…

cs.LG2016

Neural Autoregressive Distribution Estimation

Benigno Uria, Marc-Alexandre Côté, Karol Gregor +2

We present Neural Autoregressive Distribution Estimation (NADE) models, which are neural network architectures applied to the problem of unsupervised distribution and density estim…

stat.ML2016

Towards Conceptual Compression

Karol Gregor, Frederic Besse, Danilo Jimenez Rezende +2

We introduce a simple recurrent variational auto-encoder architecture that significantly improves image modeling. The system represents the state-of-the-art in latent variable mode…

stat.ML2016

One-Shot Generalization in Deep Generative Models

Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka +2

Humans have an impressive ability to reason about new concepts and experiences from just a single example. In particular, humans have an ability for one-shot generalization: an abi…

cs.CV2015963 cited

DRAW: A Recurrent Neural Network For Image Generation

Karol Gregor, Ivo Danihelka, Alex Graves +2

This paper introduces the Deep Recurrent Attentive Writer (DRAW) neural network architecture for image generation. DRAW networks combine a novel spatial attention mechanism that mi…