Papers
11,015 papers found
Augmented Cyclic Adversarial Learning for Low Resource Domain Adaptation
Ehsan Hosseini-Asl, Yingbo Zhou, Caiming Xiong et al.
A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs
Jack Lindsey, Samuel A. Ocko, Surya Ganguli et al.
A Universal Music Translation Network
Noam Mor, Lior Wolf, Adam Polyak et al.
AutoLoss: Learning Discrete Schedule for Alternate Optimization
Haowen Xu, Hao Zhang, Zhiting Hu et al.
Automatically Composing Representation Transformations as a Means for Generalization
Michael Chang, Abhishek Gupta, Sergey Levine et al.
Auxiliary Variational MCMC
Raza Habib, David Barber
A Variational Inequality Perspective on Generative Adversarial Networks
Gauthier Gidel, Hugo Berard, Gaëtan Vignoud et al.
BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning
Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou et al.
Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity
Thomas Miconi, Aditya Rawal, Jeff Clune et al.
BA-Net: Dense Bundle Adjustment Networks
Chengzhou Tang, Ping Tan
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
Roman Novak, Lechao Xiao, Yasaman Bahri et al.
Bayesian Policy Optimization for Model Uncertainty
Gilwoo Lee, Brian Hou, Aditya Mandalika et al.
Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods
Apratim Bhattacharyya, Mario Fritz, Bernt Schiele
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks, Thomas Dietterich
Beyond Greedy Ranking: Slate Optimization via List-CVAE
Ray Jiang, Sven Gowal, Yuqiu Qian et al.
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer
Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li et al.
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers
Yonatan Geifman, Guy Uziel, Ran El-Yaniv
Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition
Chun-Fu (Richard) Chen, Quanfu Fan, Neil Mallinar et al.
Biologically-Plausible Learning Algorithms Can Scale to Large Datasets
Will Xiao, Honglin Chen, Qianli Liao et al.
Boosting Robustness Certification of Neural Networks
Gagandeep Singh, Timon Gehr, Markus Püschel et al.
Bounce and Learn: Modeling Scene Dynamics with Real-World Bounces
Senthil Purushwalkam, Abhinav Gupta, Danny Kaufman et al.
Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension
Rajarshi Das, Tsendsuren Munkhdalai, Xingdi Yuan et al.
CAMOU: Learning Physical Vehicle Camouflages to Adversarially Attack Detectors in the Wild
Yang Zhang, Hassan Foroosh, Philip David et al.
Capsule Graph Neural Network
Zhang Xinyi, Lihui Chen
Caveats for information bottleneck in deterministic scenarios
Artemy Kolchinsky, Brendan D. Tracey, Steven Van Kuyk