Paper

  • Decomposing NeRF for Editing Via Feature Field Distillation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Decomposing NeRF for Editing Via Feature Field Distillation

    Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann p23311-23330 from Advances in Neural Information Processing Systems 35
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  • Deconfounded Representation Similarity for Comparison of Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Deconfounded Representation Similarity for Comparison of Neural Networks

    Tianyu Cui, Yogesh Kumar, Pekka Marttinen, Samuel Kaski p19138-19151 from Advances in Neural Information Processing Systems 35
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  • Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses

    Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Yakir Oz, Yaniv Nikankin, Michal Irani p51515-51535 from Advances in Neural Information Processing Systems 36
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  • Decorate3D: Text-Driven High-Quality Texture Generation for Mesh Decoration in the Wild

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Decorate3D: Text-Driven High-Quality Texture Generation for Mesh Decoration in the Wild

    Yanhui Guo, Xinxin Zuo, Peng Dai, Juwei Lu, Xiaolin Wu, Li Cheng, Youliang Yan, Songcen Xu, Xiaofei Wu p36664-36676 from Advances in Neural Information Processing Systems 36
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  • Decoupled Context Processing for Context Augmented Language Modeling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Decoupled Context Processing for Context Augmented Language Modeling

    Zonglin Li, Ruiqi Guo, Sanjiv Kumar p21698-21710 from Advances in Neural Information Processing Systems 35
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  • Decoupled Kullback-Leibler Divergence Loss

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Decoupled Kullback-Leibler Divergence Loss

    Jiequan Cui, Zhuotao Tian, Zhisheng Zhong, Xiaojuan Qi, Bei Yu, Hanwang Zhang p74461-74486 from Advances in Neural Information Processing Systems 37
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  • Decoupled Self-Supervised Learning for Graphs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Decoupled Self-Supervised Learning for Graphs

    Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang p620-634 from Advances in Neural Information Processing Systems 35
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  • Decoupling Classifier for Boosting Few-Shot Object Detection and Instance Segmentation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Decoupling Classifier for Boosting Few-Shot Object Detection and Instance Segmentation

    Bin-Bin Gao, Xiaochen Chen, Zhongyi Huang, Congchong Nie, Jun Liu, Jinxiang Lai, Guannan Jiang, Xi Wang, Chengjie Wang p18640-18652 from Advances in Neural Information Processing Systems 35
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  • Decoupling Features in Hierarchical Propagation for Video Object Segmentation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Decoupling Features in Hierarchical Propagation for Video Object Segmentation

    Zongxin Yang, Yi Yang p36324-36336 from Advances in Neural Information Processing Systems 35
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  • Decoupling Knowledge from Memorization: Retrieval-Augmented Prompt Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Decoupling Knowledge from Memorization: Retrieval-Augmented Prompt Learning

    Xiang Chen, Lei Li, Ningyu Zhang, Xiaozhuan Liang, Shumin Deng, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen p23908-23922 from Advances in Neural Information Processing Systems 35
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  • Decoupling Semantic Similarity from Spatial Alignment for Neural Networks.

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Decoupling Semantic Similarity from Spatial Alignment for Neural Networks.

    Tassilo Wald, Constantin Ulrich, Gregor Köhler, David Zimmerer, Stefan Denner, Michael Baumgartner, Fabian Isensee, Priyank Jain, Klaus Maier-Hein p48411-48447 from Advances in Neural Information Processing Systems 37
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  • DECRL: A Deep Evolutionary Clustering Jointed Temporal Knowledge Graph Representation Learning Approach

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DECRL: A Deep Evolutionary Clustering Jointed Temporal Knowledge Graph Representation Learning Approach

    Qian Chen, Ling Chen p55204-55227 from Advances in Neural Information Processing Systems 37
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