Papers
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
Blake Bordelon, Cengiz Pehlevan
Deep Linear Probe Generators for Weight Space Learning
Jonathan Kahana, Eliahu Horwitz, Imri Shuval et al.
DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL
Mathias Jackermeier, Alessandro Abate
Deeply Supervised Flow-Based Generative Models
Inkyu Shin, Chenglin Yang, Liang-Chieh Chen
DeepMesh: Auto-Regressive Artist-mesh Creation with Reinforcement Learning
Ruowen Zhao, Junliang Ye, Zhengyi Wang et al.
Deep Metric Learning for Unsupervised Remote Sensing Change Detection
Wele Gedara Chaminda Bandara, Vishal M. Patel
DeepMIM: Deep Supervision for Masked Image Modeling
Sucheng Ren, Fangyun Wei, Samuel Albanie et al.
Deep MMD Gradient Flow without adversarial training
Alexandre Galashov, Valentin De Bortoli, Arthur Gretton
Deep Multi-modal Graph Clustering via Graph Transformer Network
Qianqian Wang, Haiming Xu, Zihao Zhang et al.
Deep Networks Learn Features From Local Discontinuities in the Label Function
Prithaj Banerjee, Harish Guruprasad Ramaswamy, Mahesh Lorik Yadav et al.
Deep Neural Cellular Potts Models
Koen Minartz, Tim D’Hondt, Leon Hillmann et al.
Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation
Hao Liu, Jiahui Cheng, Wenjing Liao
Deep Non-Rigid Structure-from-Motion Revisited: Canonicalization and Sequence Modeling
Hui Deng, Jiawei Shi, Zhen Qin et al.
DeepNote: Note-Centric Deep Retrieval-Augmented Generation
Ruobing Wang, Qingfei Zhao, Yukun Yan et al.
Deep Opinion-Unaware Blind Image Quality Assessment by Learning and Adapting from Multiple Annotators
Zhihua Wang, Xuelin Liu, Jiebin Yan et al.
Deep Optimal Sensor Placement for Black Box Stochastic Simulations
Paula Cordero Encinar, Tobias Schröder, Peter Yatsyshin et al.
Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization
Antoine de Mathelin, François Deheeger, Mathilde Mougeot et al.
Deep Principal Support Vector Machines for Nonlinear Sufficient Dimension Reduction
Yinfeng Chen, Jin Liu, Rui Qiu
Deep Random Features for Scalable Interpolation of Spatiotemporal Data
Weibin Chen, Azhir Mahmood, Michel Tsamados et al.
Deep Rank-One Tensor Functional Factorization for Multi-Dimensional Data Recovery
Yanyi Li, Xi Zhang, Yisi Luo et al.
Deep Reactive Policy: Learning Reactive Manipulator Motion Planning for Dynamic Environments
Jiahui Yang, Jason Jingzhou Liu, Yulong Li et al.
Deep Reinforcement Learning for Efficient and Fair Allocation of Healthcare Resources
Yikuan Li, Chengsheng Mao, Kaixuan Huang et al.
Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes
Chen Tang, Ben Abbatematteo, Jiaheng Hu et al.
Deep Reinforcement Learning from Hierarchical Preference Design
Alexander Bukharin, Yixiao Li, Pengcheng He et al.
Deep Reinforcement Learning with Time-Scale Invariant Memory
Md Rysul Kabir, James Mochizuki-Freeman, Zoran Tiganj