Paper

  • Rethinking Alignment in Video Super-Resolution Transformers

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking Alignment in Video Super-Resolution Transformers

    Chao Dong, Jinjin Gu, Shuwei Shi, Xintao Wang, Liangbin Xie, Yujiu Yang p36081-36093 from Advances in Neural Information Processing Systems 35
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  • Rethinking and Improving Robustness of Convolutional Neural Networks: A Shapley Value-Based Approach in Frequency Domain

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking and Improving Robustness of Convolutional Neural Networks: A Shapley Value-Based Approach in Frequency Domain

    Yiting Chen, Qibing Ren, Junchi Yan p324-337 from Advances in Neural Information Processing Systems 35
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  • Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination

    Vincent CS Lee, Shirui Pan, Philip S Yu, Yu Zheng, Yizhen Zheng p10809-10820 from Advances in Neural Information Processing Systems 35
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  • Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition

    John Dickerson, Samuel Dooley, Micah Goldblum, Frank Hutter, Rhea Sukthanker, Colin White p74366-74393 from Advances in Neural Information Processing Systems 36
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  • Rethinking Conditional Diffusion Sampling with Progressive Guidance

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking Conditional Diffusion Sampling with Progressive Guidance

    Anh-Dung Dinh, Daochang Liu, Chang Xu p42285-42297 from Advances in Neural Information Processing Systems 36
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  • Rethinking Decoders for Transformer-based Semantic Segmentation: A Compression Perspective

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking Decoders for Transformer-based Semantic Segmentation: A Compression Perspective

    Chun-Guang Li, Qishuai Wen p49806-49833 from Advances in Neural Information Processing Systems 37
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  • Rethinking Deep Thinking: Stable Learning of Algorithms using Lipschitz Constraints

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking Deep Thinking: Stable Learning of Algorithms using Lipschitz Constraints

    Jay Bear, Jonathon Hare, Adam Prügel-Bennett p97027-97052 from Advances in Neural Information Processing Systems 37
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  • Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus

    Furui Liu, Leong Hou U, Yiming Wang, Kaiyan Zhao p57765-57792 from Advances in Neural Information Processing Systems 37
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  • Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting

    Longbing Cao, Jianxun Li, Jie Yang, Runze Yang p8515-8540 from Advances in Neural Information Processing Systems 37
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  • Rethinking Gauss-Newton for learning over-parameterized models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking Gauss-Newton for learning over-parameterized models

    Michael Arbel, Romain Menegaux, Pierre Wolinski p33379-33402 from Advances in Neural Information Processing Systems 36
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  • Rethinking Generalization in Few-Shot Classification

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking Generalization in Few-Shot Classification

    Tom Drummond, Mehrtash Harandi, Markus Hiller, Rongkai Ma p3582-3595 from Advances in Neural Information Processing Systems 35
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  • Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality

    Ziyao Guo, Ping Luo, Langtian Ma, Yu Qiao, Wenqi Shao, Kai Wang, Yuchen Yan, Yue Yang, Yang You, Kaipeng Zhang, Tianle Zhang, Yuchen Zhang p81677-81716 from Advances in Neural Information Processing Systems 37
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