Paper

  • Protein-Nucleic Acid Complex Modeling with Frame Averaging Transformer

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Protein-Nucleic Acid Complex Modeling with Frame Averaging Transformer

    Tinglin Huang, Zhenqiao Song, Rex Ying, Wengong Jin p127154-127180 from Advances in Neural Information Processing Systems 37
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  • ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design

    Pascal Notin, Aaron Kollasch, Daniel Ritter, Lood Van Niekerk, Steffanie Paul, Han Spinner, Nathan Rollins, Ada Shaw, Rose Orenbuch, Ruben Weitzman, Jonathan Frazer, Mafalda Dias, Dinko Franceschi, Yarin Gal, Debora Marks p64331-64379 from Advances in Neural Information Processing Systems 36
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  • ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics

    Zhangyang Gao, Cheng Tan, Yijie Zhang, Xingran Chen, Lirong Wu, Stan Z. Li p68207-68220 from Advances in Neural Information Processing Systems 36
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  • ProteinNPT: Improving Protein Property Prediction and Design with Non-Parametric Transformers

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ProteinNPT: Improving Protein Property Prediction and Design with Non-Parametric Transformers

    Pascal Notin, Ruben Weitzman, Debora Marks, Yarin Gal p33529-33563 from Advances in Neural Information Processing Systems 36
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  • ProteinShake: Building datasets and benchmarks for deep learning on protein structures

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ProteinShake: Building datasets and benchmarks for deep learning on protein structures

    Tim Kucera, Carlos Oliver, Dexiong Chen, Karsten Borgwardt p58277-58289 from Advances in Neural Information Processing Systems 36
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  • PROTES: Probabilistic Optimization with Tensor Sampling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    PROTES: Probabilistic Optimization with Tensor Sampling

    Anastasiia Batsheva, Andrei Chertkov, Gleb Ryzhakov, Ivan Oseledets p808-823 from Advances in Neural Information Processing Systems 36
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  • ProtGO: Function-Guided Protein Modeling for Unified Representation Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ProtGO: Function-Guided Protein Modeling for Unified Representation Learning

    Bozhen Hu, Cheng Tan, Yongjie Xu, Zhangyang Gao, Jun Xia, Lirong Wu, Stan Z. Li p88581-88604 from Advances in Neural Information Processing Systems 37
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  • PROTOCOLS AND RESULTS ANALYSIS METHODS FOR CYCLIC TESTS OF TIMBER JOINTS. A DISCUSSION

    World Conference on Timber Engineering 2023 (WCTE 2023)

    PROTOCOLS AND RESULTS ANALYSIS METHODS FOR CYCLIC TESTS OF TIMBER JOINTS. A DISCUSSION

    Meta Kržan, Caroline D. Aquino, Michael Schweigler, Zheng Li, Jorge M. Branco p3685-3693 from World Conference on Timber Engineering (WCTE 2023)
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  • ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion

    Yingjun Du, Zehao Xiao, Shengcai Liao, Cees Snoek p46304-46322 from Advances in Neural Information Processing Systems 36
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  • Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval

    Hao Li, Jingkuan Song, Lianli Gao, Xiaosu Zhu, Hengtao Shen p24564-24585 from Advances in Neural Information Processing Systems 36
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  • Prototypical Hash Encoding for On-the-Fly Fine-Grained Category Discovery

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Prototypical Hash Encoding for On-the-Fly Fine-Grained Category Discovery

    Haiyang Zheng, Nan Pu, Wenjing Li, Nicu Sebe, Zhun Zhong p101428-101455 from Advances in Neural Information Processing Systems 37
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  • Prototypical Variational Autoencoder for 3D Few-shot Object Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Prototypical Variational Autoencoder for 3D Few-shot Object Detection

    Weiliang Tang, Biqi Yang, Xianzhi Li, Yun-Hui Liu, Pheng-Ann Heng, Chi-Wing Fu p2566-2579 from Advances in Neural Information Processing Systems 36
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