Papers
11,951 papers found
Discrete Copula Diffusion
Anji Liu, Oliver Broadrick, Mathias Niepert et al.
Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation
Jun Hyeong Kim, Seonghwan Kim, Seokhyun Moon et al.
Discrete Distribution Networks
Lei Yang
Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control
Songyuan Zhang, Oswin So, Mitchell Black et al.
Discrete Latent Plans via Semantic Skill Abstractions
Haobin Jiang, Jiangxing Wang, Zongqing Lu
Discretization-invariance? On the Discretization Mismatch Errors in Neural Operators
Wenhan Gao, Ruichen Xu, Yuefan Deng et al.
Discriminating image representations with principal distortions
Jenelle Feather, David Lipshutz, Sarah E Harvey et al.
Discriminator-Guided Embodied Planning for LLM Agent
Haofu Qian, Chenjia Bai, Jiatao Zhang et al.
Disentangled Representation Learning with the Gromov-Monge Gap
Théo Uscidda, Luca Eyring, Karsten Roth et al.
Disentangling 3D Animal Pose Dynamics with Scrubbed Conditional Latent Variables
Joshua Huang Wu, Hari Koneru, James Russell Ravenel et al.
Disentangling Representations through Multi-task Learning
Pantelis Vafidis, Aman Bhargava, Antonio Rangel
DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation
Jing He, Haodong Li, huyongzhe et al.
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction
Xinwei Zhang, Zhiqi Bu, Borja Balle et al.
DisPose: Disentangling Pose Guidance for Controllable Human Image Animation
Hongxiang Li, Yaowei Li, Yuhang Yang et al.
Dissecting Adversarial Robustness of Multimodal LM Agents
Chen Henry Wu, Rishi Rajesh Shah, Jing Yu Koh et al.
Distance-Based Tree-Sliced Wasserstein Distance
Hoang V. Tran, Minh-Khoi Nguyen-Nhat, Huyen Trang Pham et al.
Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching
Enshu Liu, Xuefei Ning, Yu Wang et al.
DistillHGNN: A Knowledge Distillation Approach for High-Speed Hypergraph Neural Networks
Saman Forouzandeh, Parham Moradi DW, Mahdi Jalili
Distilling Dataset into Neural Field
Donghyeok Shin, HeeSun Bae, Gyuwon Sim et al.
Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning
Jaehyeon Son, Soochan Lee, Gunhee Kim
Distilling Structural Representations into Protein Sequence Models
Jeffrey Ouyang-Zhang, Chengyue Gong, Yue Zhao et al.
Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint
Guangkun Nie, Gongzheng Tang, Shenda Hong
Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference
Nadav Timor, Jonathan Mamou, Daniel Korat et al.
Distributional Associations vs In-Context Reasoning: A Study of Feed-forward and Attention Layers
Lei Chen, Joan Bruna, Alberto Bietti
Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation
Shengyuan Zhang, Ling Yang, Zejian Li et al.