Andrew Brock | DeepAI

DeepAI AI Chat

Featured Co-authors

Andrew Zisserman
187 publications
Yee Whye Teh
122 publications
Quoc V. Le
113 publications
Oriol Vinyals
101 publications
Pushmeet Kohli
93 publications
Razvan Pascanu
87 publications
Michal Valko
73 publications
Karen Simonyan
53 publications
Raia Hadsell
41 publications
Jost Tobias Springenberg
39 publications
Aaron van den Oord
37 publications

∙ 02/20/2023

Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation

Skip connections and normalisation layers form two standard architectura...

0 Bobby He, et al. ∙

∙ 04/29/2022

Flamingo: a Visual Language Model for Few-Shot Learning

Building models that can be rapidly adapted to numerous tasks using only...

7 Jean-Baptiste Alayrac, et al. ∙

∙ 11/23/2021

Towards Learning Universal Audio Representations

The ability to learn universal audio representations that can solve dive...

0 Luyu Wang, et al. ∙

∙ 07/30/2021

Perceiver IO: A General Architecture for Structured Inputs Outputs

The recently-proposed Perceiver model obtains good results on several do...

6 Andrew Jaegle, et al. ∙

∙ 05/27/2021

Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error

In computer vision, it is standard practice to draw a single sample from...

0 Stanislav Fort, et al. ∙

∙ 04/02/2021

Skillful Precipitation Nowcasting using Deep Generative Models of Radar

Precipitation nowcasting, the high-resolution forecasting of precipitati...

6 Suman Ravuri, et al. ∙

∙ 03/04/2021

Perceiver: General Perception with Iterative Attention

Biological systems understand the world by simultaneously processing hig...

18 Andrew Jaegle, et al. ∙

∙ 02/11/2021

High-Performance Large-Scale Image Recognition Without Normalization

Batch normalization is a key component of most image classification mode...

0 Andrew Brock, et al. ∙

∙ 01/21/2021

Characterizing signal propagation to close the performance gap in unnormalized ResNets

Batch Normalization is a key component in almost all state-of-the-art im...

0 Andrew Brock, et al. ∙

∙ 10/28/2020

Training Generative Adversarial Networks by Solving Ordinary Differential Equations

The instability of Generative Adversarial Network (GAN) training has fre...

21 Chongli Qin, et al. ∙

∙ 10/20/2020

BYOL works even without batch statistics

Bootstrap Your Own Latent (BYOL) is a self-supervised learning approach ...

0 Pierre H. Richemond, et al. ∙

∙ 04/06/2020

Evolving Normalization-Activation Layers

Normalization layers and activation functions are critical components in...

9 Hanxiao Liu, et al. ∙

∙ 09/28/2018

Large Scale GAN Training for High Fidelity Natural Image Synthesis

Despite recent progress in generative image modeling, successfully gener...

2 Andrew Brock, et al. ∙

∙ 06/15/2017

FreezeOut: Accelerate Training by Progressively Freezing Layers

The early layers of a deep neural net have the fewest parameters, but ta...

0 Andrew Brock, et al. ∙

∙ 09/22/2016

Neural Photo Editing with Introspective Adversarial Networks

The increasingly photorealistic sample quality of generative image model...

0 Andrew Brock, et al. ∙

∙ 08/15/2016

Generative and Discriminative Voxel Modeling with Convolutional Neural Networks

When working with three-dimensional data, choice of representation is ke...

0 Andrew Brock, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world