Papers
Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement
Miao Zhang, Huiqi Li, Shirui Pan et al.
Differentiable Top-k with Optimal Transport
Yujia Xie, Hanjun Dai, Minshuo Chen et al.
Differentially Private Clustering: Tight Approximation Ratios
Badih Ghazi, Ravi Kumar, Pasin Manurangsi
Differentially-Private Federated Linear Bandits
Abhimanyu Dubey, Alex `Sandy' Pentland
DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling
Moshe Eliasof, Eran Treister
Digraph Inception Convolutional Networks
Zekun Tong, Yuxuan Liang, Changsheng Sun et al.
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures
Julien Launay, Iacopo Poli, François Boniface et al.
Directional convergence and alignment in deep learning
Ziwei Ji, Matus J. Telgarsky
Directional Pruning of Deep Neural Networks
Shih-Kang Chao, Zhanyu Wang, Yue Xing et al.
Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces
Guy Lorberbom, Chris J Maddison, Nicolas Heess et al.
Dirichlet Graph Variational Autoencoder
Jia Li, Jianwei Yu, Jiajin Li et al.
DisARM: An Antithetic Gradient Estimator for Binary Latent Variables
Zhe Dong, Andriy Mnih, George Tucker
DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction
Aviral Kumar, Abhishek Gupta, Sergey Levine
Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation
KwanYong Park, Sanghyun Woo, Inkyu Shin et al.
Discovering conflicting groups in signed networks
Ruo-Chun Tzeng, Bruno Ordozgoiti, Aristides Gionis
Discovering Reinforcement Learning Algorithms
Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki et al.
Discovering Symbolic Models from Deep Learning with Inductive Biases
Miles Cranmer, Alvaro Sanchez Gonzalez, Peter Battaglia et al.
Discriminative Sounding Objects Localization via Self-supervised Audiovisual Matching
Di Hu, Rui Qian, Minyue Jiang et al.
Disentangling by Subspace Diffusion
David Pfau, Irina Higgins, Alex Botev et al.
Disentangling Human Error from Ground Truth in Segmentation of Medical Images
Le Zhang, Ryutaro Tanno, Mou-Cheng Xu et al.
DISK: Learning local features with policy gradient
Michał Tyszkiewicz, Pascal Fua, Eduard Trulls
Displacement-Invariant Matching Cost Learning for Accurate Optical Flow Estimation
Jianyuan Wang, Yiran Zhong, Yuchao Dai et al.
Dissecting Neural ODEs
Stefano Massaroli, Michael Poli, Jinkyoo Park et al.
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning
Pan Li, Yanbang Wang, Hongwei Wang et al.
Distributed Distillation for On-Device Learning
Ilai Bistritz, Ariana Mann, Nicholas Bambos