Papers
11,951 papers found
Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection
Bo Zong, Qi Song, Martin Renqiang Min et al.
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling
Carlos Riquelme, George Tucker, Jasper Snoek
Deep, complex, invertible networks for inversion of transmission effects in multimode optical fibres
Oisín Moran, Piergiorgio Caramazza, Daniele Faccio et al.
Deep Complex Networks
Chiheb Trabelsi, Olexa Bilaniuk, Ying Zhang et al.
Deep contextualized word representations
Matthew E Peters, Mark Neumann, Mohit Iyyer et al.
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
Aleksandar Bojchevski, Stephan Günnemann
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
Yujun Lin, Song Han, Huizi Mao et al.
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design
Yoav Levine, David Yakira, Nadav Cohen et al.
Deep Learning as a Mixed Convex-Combinatorial Optimization Problem
Abram L. Friesen, Pedro Domingos
Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge
Emmanuel de Bezenac, Arthur Pajot, Patrick Gallinari
Deep Learning with Logged Bandit Feedback
Thorsten Joachims, Adith Swaminathan, Maarten de Rijke
Deep Neural Networks as Gaussian Processes
Jaehoon Lee, Yasaman Bahri, Roman Novak et al.
DeepProbLog: Neural Probabilistic Logic Programming
Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig et al.
Deep Rewiring: Training very sparse deep networks
Guillaume Bellec, David Kappel, Wolfgang Maass et al.
Deep Sensing: Active Sensing using Multi-directional Recurrent Neural Networks
Jinsung Yoon, William R. Zame, Mihaela van der Schaar
Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning
Wei Ping, Kainan Peng, Andrew Gibiansky et al.
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models
Pouya Samangouei, Maya Kabkab, Rama Chellappa
Demystifying MMD GANs
Mikołaj Bińkowski, Danica J. Sutherland, Michael Arbel et al.
Detecting Statistical Interactions from Neural Network Weights
Michael Tsang, Dehua Cheng, Yan Liu
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
Yaguang Li, Rose Yu, Cyrus Shahabi et al.
Distributed Distributional Deterministic Policy Gradients
Gabriel Barth-Maron, Matthew W. Hoffman, David Budden et al.
Distributed Fine-tuning of Language Models on Private Data
Vadim Popov, Mikhail Kudinov, Irina Piontkovskaya et al.
Distributed Prioritized Experience Replay
Dan Horgan, John Quan, David Budden et al.
Divide and Conquer Networks
Alex Nowak, David Folqué, Joan Bruna