1.3k citations · 1.4k across the 13 of their papers we have counts for
13 papers
Objects of violence: synthetic data for practical ML in human rights investigations
Lachlan Kermode, Jan Freyberg, Alican Akturk +5
We introduce a machine learning workflow to search for, identify, and meaningfully triage videos and images of munitions, weapons, and military equipment, even when limited trainin…
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery
Michel Deudon, Alfredo Kalaitzis, Israel Goytom +7
Generative deep learning has sparked a new wave of Super-Resolution (SR) algorithms that enhance single images with impressive aesthetic results, albeit with imaginary details. Mul…
DECoVaC: Design of Experiments with Controlled Variability Components
Thomas Boquet, Laure Delisle, Denis Kochetkov +4
Reproducible research in Machine Learning has seen a salutary abundance of progress lately: workflows, transparency, and statistical analysis of validation and test performance. We…
A large-scale crowdsourced analysis of abuse against women journalists and politicians on Twitter
Laure Delisle, Alfredo Kalaitzis, Krzysztof Majewski +3
We report the first, to the best of our knowledge, hand-in-hand collaboration between human rights activists and machine learners, leveraging crowd-sourcing to study online abuse a…
Approximate Hubel-Wiesel Modules and the Data Structures of Neural Computation
Joel Z. Leibo, Julien Cornebise, Sergio Gómez +1
This paper describes a framework for modeling the interface between perception and memory on the algorithmic level of analysis. It is consistent with phenomena associated with many…
Weight Uncertainty in Neural Networks
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu +1
We introduce a new, efficient, principled and backpropagation-compatible algorithm for learning a probability distribution on the weights of a neural network, called Bayes by Backp…