output
20022025
most citedGW190814: Gravitational Waves from the Coalescence of a 23 M Black Hole with a 2.6 M Compact Object

1.8k citations

Showing 2017Show all

46 papers · 1 filter

math.HO201711 cited

Cauchy, infinitesimals and ghosts of departed quantifiers

Jacques Bair, Piotr Blaszczyk, Robert Ely +10

Procedures relying on infinitesimals in Leibniz, Euler and Cauchy have been interpreted in both a Weierstrassian and Robinson's frameworks. The latter provides closer proxies for t…

cs.NE201744 cited

DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess

Eli David, Nathan S. Netanyahu, Lior Wolf

We present an end-to-end learning method for chess, relying on deep neural networks. Without any a priori knowledge, in particular without any knowledge regarding the rules of ches…

cs.CV20174 cited

DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders

Ido Cohen, Eli David, Nathan S. Netanyahu +2

This paper presents a novel deep learning-based method for learning a functional representation of mammalian neural images. The method uses a deep convolutional denoising autoencod…

cs.CV201747 cited

DeepPainter: Painter Classification Using Deep Convolutional Autoencoders

Eli David, Nathan S. Netanyahu

In this paper we describe the problem of painter classification, and propose a novel approach based on deep convolutional autoencoder neural networks. While previous approaches rel…

cs.CV20178 cited

DNN-Buddies: A Deep Neural Network-Based Estimation Metric for the Jigsaw Puzzle Problem

Dror Sholomon, Eli David, Nathan S. Netanyahu

This paper introduces the first deep neural network-based estimation metric for the jigsaw puzzle problem. Given two puzzle piece edges, the neural network predicts whether or not…

cs.CR2017224 cited

DeepSign: Deep Learning for Automatic Malware Signature Generation and Classification

Eli David, Nathan S. Netanyahu

This paper presents a novel deep learning based method for automatic malware signature generation and classification. The method uses a deep belief network (DBN), implemented with…