activity
20132023
most citedA simple neural network module for relational reasoning

503 citations · 1.3k across the 34 of their papers we have counts for

collaborators
Showing 2018Show all

8 papers · 1 filter

cs.LG2018★ 1 cited

Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning

Aishwarya Agrawal, Mateusz Malinowski, Felix Hill +3

Advances in Deep Reinforcement Learning have led to agents that perform well across a variety of sensory-motor domains. In this work, we study the setting in which an agent must le…

cs.LG2018★ 14 cited

Playing the Game of Universal Adversarial Perturbations

Julien Perolat, Mateusz Malinowski, Bilal Piot +1

We study the problem of learning classifiers robust to universal adversarial perturbations. While prior work approaches this problem via robust optimization, adversarial training,…

cs.CV2018★ 10 cited

The Visual QA Devil in the Details: The Impact of Early Fusion and Batch Norm on CLEVR

Mateusz Malinowski, Carl Doersch

Visual QA is a pivotal challenge for higher-level reasoning, requiring understanding language, vision, and relationships between many objects in a scene. Although datasets like CLE…

cs.CV2018★ 10 cited

Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions

M. Wagner, H. Basevi, R. Shetty +4

In-depth scene descriptions and question answering tasks have greatly increased the scope of today's definition of scene understanding. While such tasks are in principle open ended…

cs.CV2018★ 9 cited

Learning Visual Question Answering by Bootstrapping Hard Attention

Mateusz Malinowski, Carl Doersch, Adam Santoro +1

Attention mechanisms in biological perception are thought to select subsets of perceptual information for more sophisticated processing which would be prohibitive to perform on all…

cs.LG2018

Relational inductive biases, deep learning, and graph networks

Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst +24

Artificial intelligence (AI) has undergone a renaissance recently, making major progress in key domains such as vision, language, control, and decision-making. This has been due, i…

cs.NE2018★ 47 cited

Hyperbolic Attention Networks

Caglar Gulcehre, Misha Denil, Mateusz Malinowski +8

We introduce hyperbolic attention networks to endow neural networks with enough capacity to match the complexity of data with hierarchical and power-law structure. A few recent app…

cs.AI2018★ 52 cited

Learning to Navigate in Cities Without a Map

Piotr Mirowski, Matthew Koichi Grimes, Mateusz Malinowski +7

Navigating through unstructured environments is a basic capability of intelligent creatures, and thus is of fundamental interest in the study and development of artificial intellig…