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, Wengong Jin, Zhenqiao Song, Rex Ying 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

    Mafalda Dias, Dinko Franceschi, Jonathan Frazer, Yarin Gal, Aaron Kollasch, Debora Marks, Pascal Notin, Rose Orenbuch, Steffanie Paul, Daniel Ritter, Nathan Rollins, Ada Shaw, Han Spinner, Lood Van Niekerk, Ruben Weitzman 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

    Xingran Chen, Zhangyang Gao, Stan Z. Li, Cheng Tan, Lirong Wu, Yijie Zhang 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

    Yarin Gal, Debora Marks, Pascal Notin, Ruben Weitzman 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

    Karsten Borgwardt, Dexiong Chen, Tim Kucera, Carlos Oliver 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, Ivan Oseledets, Gleb Ryzhakov 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

    Zhangyang Gao, Bozhen Hu, Stan Z. Li, Cheng Tan, Lirong Wu, Jun Xia, Yongjie Xu 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, Shengcai Liao, Cees Snoek, Zehao Xiao 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

    Lianli Gao, Hao Li, Hengtao Shen, Jingkuan Song, Xiaosu Zhu 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

    Wenjing Li, Nan Pu, Nicu Sebe, Haiyang Zheng, 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

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