Papers
11,951 papers found
Convolutional Neural Networks on Non-uniform Geometrical Signals Using Euclidean Spectral Transformation
Chiyu Max Jiang, Dequan Wang, Jingwei Huang et al.
Cost-Sensitive Robustness against Adversarial Examples
Xiao Zhang, David Evans
Critical Learning Periods in Deep Networks
Alessandro Achille, Matteo Rovere, Stefano Soatto
DARTS: Differentiable Architecture Search
Hanxiao Liu, Karen Simonyan, Yiming Yang
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds
Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski et al.
Decoupled Weight Decay Regularization
Ilya Loshchilov, Frank Hutter
Deep Anomaly Detection with Outlier Exposure
Dan Hendrycks, Mantas Mazeika, Thomas Dietterich
Deep Convolutional Networks as shallow Gaussian Processes
Adrià Garriga-Alonso, Carl Edward Rasmussen, Laurence Aitchison
Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks
Reinhard Heckel, Paul Hand
Deep Frank-Wolfe For Neural Network Optimization
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
Deep Graph Infomax
Petar Veličković, William Fedus, William L. Hamilton et al.
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
Michael Lutter, Christian Ritter, Jan Peters
Deep Layers as Stochastic Solvers
Adel Bibi, Bernard Ghanem, Vladlen Koltun et al.
Deep Learning 3D Shapes Using Alt-az Anisotropic 2-Sphere Convolution
Min Liu, Fupin Yao, Chiho Choi et al.
Deep learning generalizes because the parameter-function map is biased towards simple functions
Guillermo Valle-Perez, Chico Q. Camargo, Ard A. Louis
DeepOBS: A Deep Learning Optimizer Benchmark Suite
Frank Schneider, Lukas Balles, Philipp Hennig
Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL
Anusha Nagabandi, Chelsea Finn, Sergey Levine
Deep reinforcement learning with relational inductive biases
Vinicius Zambaldi, David Raposo, Adam Santoro et al.
Defensive Quantization: When Efficiency Meets Robustness
Ji Lin, Chuang Gan, Song Han
DELTA: DEEP LEARNING TRANSFER USING FEATURE MAP WITH ATTENTION FOR CONVOLUTIONAL NETWORKS
Xingjian Li, Haoyi Xiong, Hanchao Wang et al.
Detecting Egregious Responses in Neural Sequence-to-sequence Models
Tianxing He, James Glass
Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience
Vaishnavh Nagarajan, Zico Kolter
Deterministic Variational Inference for Robust Bayesian Neural Networks
Anqi Wu, Sebastian Nowozin, Edward Meeds et al.
DHER: Hindsight Experience Replay for Dynamic Goals
Meng Fang, Cheng Zhou, Bei Shi et al.