Papers
11,015 papers found
Discovering Motor Programs by Recomposing Demonstrations
Tanmay Shankar, Shubham Tulsiani, Lerrel Pinto et al.
Discrepancy Ratio: Evaluating Model Performance When Even Experts Disagree on the Truth
Igor Lovchinsky, Alon Daks, Israel Malkin et al.
Discriminative Particle Filter Reinforcement Learning for Complex Partial observations
Xiao Ma, Peter Karkus, David Hsu et al.
Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)
Peter Sorrenson, Carsten Rother, Ullrich Köthe
Disentangling Factors of Variations Using Few Labels
Francesco Locatello, Michael Tschannen, Stefan Bauer et al.
Disentangling neural mechanisms for perceptual grouping
Junkyung Kim*, Drew Linsley*, Kalpit Thakkar et al.
Distance-Based Learning from Errors for Confidence Calibration
Chen Xing, Sercan Arik, Zizhao Zhang et al.
Distributed Bandit Learning: Near-Optimal Regret with Efficient Communication
Yuanhao Wang, Jiachen Hu, Xiaoyu Chen et al.
Distributionally Robust Neural Networks
Shiori Sagawa*, Pang Wei Koh*, Tatsunori B. Hashimoto et al.
Diverse Trajectory Forecasting with Determinantal Point Processes
Ye Yuan, Kris M. Kitani
DivideMix: Learning with Noisy Labels as Semi-supervised Learning
Junnan Li, Richard Socher, Steven C.H. Hoi
Domain Adaptive Multibranch Networks
Róger Bermúdez-Chacón, Mathieu Salzmann, Pascal Fua
Don't Use Large Mini-batches, Use Local SGD
Tao Lin, Sebastian U. Stich, Kumar Kshitij Patel et al.
Double Neural Counterfactual Regret Minimization
Hui Li, Kailiang Hu, Shaohua Zhang et al.
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation
Ziyang Tang*, Yihao Feng*, Lihong Li et al.
Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks
Haoran You, Chaojian Li, Pengfei Xu et al.
Dream to Control: Learning Behaviors by Latent Imagination
Danijar Hafner, Timothy Lillicrap, Jimmy Ba et al.
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
Yu Rong, Wenbing Huang, Tingyang Xu et al.
Duration-of-Stay Storage Assignment under Uncertainty
Michael Lingzhi Li, Elliott Wolf, Daniel Wintz
Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery
Kristian Hartikainen, Xinyang Geng, Tuomas Haarnoja et al.
Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning
Xiaoran Xu, Wei Feng, Yunsheng Jiang et al.
Dynamic Model Pruning with Feedback
Tao Lin, Sebastian U. Stich, Luis Barba et al.
Dynamics-Aware Embeddings
William Whitney, Rajat Agarwal, Kyunghyun Cho et al.
Dynamics-Aware Unsupervised Discovery of Skills
Archit Sharma, Shixiang Gu, Sergey Levine et al.
Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers
Junjie LIU, Zhe XU, Runbin SHI et al.