User profiles for I. Goodfellow
Ian GoodfellowDeepMind Verified email at deepmind.com Cited by 284180 |
Goodfellow I
PA Goodfellow, X Mirza… - Pouget-Abadie J …, 2014 - springfieldsfirstschool.org.uk
E Goodfellow Page 1 SPRINGFIELDS FIRST SCHOOL Yarnfield, Stone, Staffordshire, ST15
0NJ ‘ACHIEVING EXCELLENCE TOGETHER’ Headteacher Telephone: 01785 337310 Alison …
0NJ ‘ACHIEVING EXCELLENCE TOGETHER’ Headteacher Telephone: 01785 337310 Alison …
Generative adversarial networks
Generative adversarial networks are a kind of artificial intelligence algorithm designed to
solve the generative modeling problem. The goal of a generative model is to study a collection …
solve the generative modeling problem. The goal of a generative model is to study a collection …
[BOOK][B] Deep learning
An introduction to a broad range of topics in deep learning, covering mathematical and
conceptual background, deep learning techniques used in industry, and research perspectives.“…
conceptual background, deep learning techniques used in industry, and research perspectives.“…
Generative adversarial nets
I Goodfellow, J Pouget-Abadie… - Advances in neural …, 2014 - proceedings.neurips.cc
We propose a new framework for estimating generative models via adversarial nets, in
which we simultaneously train two models: a generative model G that captures the data …
which we simultaneously train two models: a generative model G that captures the data …
[BOOK][B] Deep learning
Inventors have long dreamed of creating machines that think. Ancient Greek myths tell of
intelligent objects, such as animated statues of human beings and tables that arrive full of food …
intelligent objects, such as animated statues of human beings and tables that arrive full of food …
Explaining and harnessing adversarial examples
Several machine learning models, including neural networks, consistently misclassify adversarial
examples---inputs formed by applying small but intentionally worst-case perturbations …
examples---inputs formed by applying small but intentionally worst-case perturbations …
Maxout networks
We consider the problem of designing models to leverage a recently introduced approximate
model averaging technique called dropout. We define a simple new model called maxout (…
model averaging technique called dropout. We define a simple new model called maxout (…
Improved techniques for training gans
We present a variety of new architectural features and training procedures that we apply to
the generative adversarial networks (GANs) framework. Using our new techniques, we …
the generative adversarial networks (GANs) framework. Using our new techniques, we …
Theano: A Python framework for fast computation of mathematical expressions
Theano is a Python library that allows to define, optimize, and evaluate mathematical expressions
involving multi-dimensional arrays efficiently. Since its introduction, it has been one of …
involving multi-dimensional arrays efficiently. Since its introduction, it has been one of …
Adversarial machine learning at scale
Adversarial examples are malicious inputs designed to fool machine learning models. They
often transfer from one model to another, allowing attackers to mount black box attacks …
often transfer from one model to another, allowing attackers to mount black box attacks …