Papers
11,015 papers found
Kernel RNN Learning (KeRNL)
Christopher Roth, Ingmar Kanitscheider, Ila Fiete
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning
Pramod Kaushik Mudrakarta, Mark Sandler, Andrey Zhmoginov et al.
KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks
James Jordon, Jinsung Yoon, Mihaela van der Schaar
Knowledge Flow: Improve Upon Your Teachers
Iou-Jen Liu, Jian Peng, Alexander Schwing
L2-Nonexpansive Neural Networks
Haifeng Qian, Mark N. Wegman
Label super-resolution networks
Kolya Malkin, Caleb Robinson, Le Hou et al.
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders
Junxian He, Daniel Spokoyny, Graham Neubig et al.
LanczosNet: Multi-Scale Deep Graph Convolutional Networks
Renjie Liao, Zhizhen Zhao, Raquel Urtasun et al.
Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation
Sang-Woo Lee, Tong Gao, Sohee Yang et al.
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Andrew Brock, Jeff Donahue, Karen Simonyan
Large Scale Graph Learning From Smooth Signals
Vassilis Kalofolias, Nathanaël Perraudin
Large-Scale Study of Curiosity-Driven Learning
Yuri Burda, Harri Edwards, Deepak Pathak et al.
Latent Convolutional Models
ShahRukh Athar, Evgeny Burnaev, Victor Lempitsky
LayoutGAN: Generating Graphic Layouts with Wireframe Discriminators
Jianan Li, Jimei Yang, Aaron Hertzmann et al.
Learnable Embedding Space for Efficient Neural Architecture Compression
Shengcao Cao, Xiaofang Wang, Kris M. Kitani
Learning Actionable Representations with Goal Conditioned Policies
Dibya Ghosh, Abhishek Gupta, Sergey Levine
Learning a Meta-Solver for Syntax-Guided Program Synthesis
Xujie Si, Yuan Yang, Hanjun Dai et al.
Learning a SAT Solver from Single-Bit Supervision
Daniel Selsam, Matthew Lamm, Benedikt B\"{u}nz et al.
Learning-Based Frequency Estimation Algorithms
Chen-Yu Hsu, Piotr Indyk, Dina Katabi et al.
Learning concise representations for regression by evolving networks of trees
William La Cava, Tilak Raj Singh, James Taggart et al.
Learning deep representations by mutual information estimation and maximization
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon et al.
Learning Embeddings into Entropic Wasserstein Spaces
Charlie Frogner, Farzaneh Mirzazadeh, Justin Solomon
Learning Exploration Policies for Navigation
Tao Chen, Saurabh Gupta, Abhinav Gupta
Learning Factorized Multimodal Representations
Yao-Hung Hubert Tsai, Paul Pu Liang, Amir Zadeh et al.
LEARNING FACTORIZED REPRESENTATIONS FOR OPEN-SET DOMAIN ADAPTATION
Mahsa Baktashmotlagh, Masoud Faraki, Tom Drummond et al.