Paper

  • Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence

    Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, Trevor Darrell p47500-47510 from Advances in Neural Information Processing Systems 36
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  • Diffusion Imitation from Observation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion Imitation from Observation

    Bo-Ruei Huang, Chun-Kai Yang, Chun-Mao Lai, Dai-Jie Wu, Shao-Hua Sun p137190-137217 from Advances in Neural Information Processing Systems 37
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  • Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks

    Xin Yan, Hui Fang, Qiang He p22326-22350 from Advances in Neural Information Processing Systems 36
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  • Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning

    Haoran He, Chenjia Bai, Kang Xu, Zhuoran Yang, Weinan Zhang, Dong Wang, Bin Zhao, Xuelong Li p64896-64917 from Advances in Neural Information Processing Systems 36
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  • Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement

    Tao Yang, Cuiling Lan, Yan Lu, Nanning Zheng p82465-82492 from Advances in Neural Information Processing Systems 37
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  • Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels

    Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li, Jun Zhu p43479-43495 from Advances in Neural Information Processing Systems 36
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  • Diffusion Models are Certifiably Robust Classifiers

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion Models are Certifiably Robust Classifiers

    Huanran Chen, Yinpeng Dong, Shitong Shao, Zhongkai Hao, Xiao Yang, Hang Su, Jun Zhu p50062-50097 from Advances in Neural Information Processing Systems 37
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  • Diffusion Models as Plug-And-Play Priors

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion Models as Plug-And-Play Priors

    Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras p14715-14728 from Advances in Neural Information Processing Systems 35
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  • Diffusion Models With Learned Adaptive Noise

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion Models With Learned Adaptive Noise

    Subham Sahoo, Aaron Gokaslan, Chris De, Volodymyr Kuleshov p105730-105779 from Advances in Neural Information Processing Systems 37
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  • Diffusion of Thought: Chain-of-Thought Reasoning in Diffusion Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion of Thought: Chain-of-Thought Reasoning in Diffusion Language Models

    Jiacheng Ye, Shansan Gong, Liheng Chen, Lin Zheng, Jiahui Gao, Han Shi, Chuan Wu, Xin Jiang, Zhenguo Li, Wei Bi, Lingpeng Kong p105345-105374 from Advances in Neural Information Processing Systems 37
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  • Diffusion PID: Interpreting Diffusion via Partial Information Decomposition

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion PID: Interpreting Diffusion via Partial Information Decomposition

    Shaurya Dewan, Rushikesh Zawar, Prakanshul Saxena, Yingshan Chang, Andrew Luo, Yonatan Bisk p2045-2079 from Advances in Neural Information Processing Systems 37
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  • Diffusion Policies Creating a Trust Region for Offline Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diffusion Policies Creating a Trust Region for Offline Reinforcement Learning

    Tianyu Chen, Zhendong Wang, Mingyuan Zhou p50098-50125 from Advances in Neural Information Processing Systems 37
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