Paper

  • Normalizing Flows for Knockoff-Free Controlled Feature Selection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Normalizing Flows for Knockoff-Free Controlled Feature Selection

    Derek Hansen, Brian Manzo, Jeffrey Regier p16125-16137 from Advances in Neural Information Processing Systems 35
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  • Not All Bits Have Equal Value: Heterogeneous Precisions Via Trainable Noise

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Not All Bits Have Equal Value: Heterogeneous Precisions Via Trainable Noise

    Pedro Savarese, Xin Yuan, Yanjing Li, Michael Maire p35769-35782 from Advances in Neural Information Processing Systems 35
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  • Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features

    Benyuan Meng, Qianqian Xu, Zitai Wang, Xiaochun Cao, Qingming Huang p55141-55177 from Advances in Neural Information Processing Systems 37
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  • Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts

    Emanuele Marconato, Stefano Teso, Antonio Vergari, Andrea Passerini p72507-72539 from Advances in Neural Information Processing Systems 36
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  • Not All Out-of-Distribution Data Are Harmful to Open-Set Active Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Not All Out-of-Distribution Data Are Harmful to Open-Set Active Learning

    Yang Yang, Yuxuan Zhang, Xin Song, Yi Xu p13802-13818 from Advances in Neural Information Processing Systems 36
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  • Not All Tokens Are What You Need for Pretraining

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Not All Tokens Are What You Need for Pretraining

    Zhenghao Lin, Zhibin Gou, Yeyun Gong, Xiao Liu, Yelong Shen, Ruochen Xu, Chen Lin, Yujiu Yang, Jian Jiao, Nan Duan, Weizhu Chen p29029-29063 from Advances in Neural Information Processing Systems 37
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  • Not Just Object, But State: Compositional Incremental Learning without Forgetting

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Not Just Object, But State: Compositional Incremental Learning without Forgetting

    Yanyi Zhang, Binglin Qiu, Qi Jia, Yu Liu, Ran He p123182-123206 from Advances in Neural Information Processing Systems 37
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  • Not so griddy: Internal representations of RNNs path integrating more than one agent

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Not so griddy: Internal representations of RNNs path integrating more than one agent

    William Redman, Francisco Acosta, Santiago Acosta-Mendoza, Nina Miolane p22657-22689 from Advances in Neural Information Processing Systems 37
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  • Not Too Little, Not Too Much: A Theoretical Analysis of Graph (over)smoothing

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Not Too Little, Not Too Much: A Theoretical Analysis of Graph (over)smoothing

    Nicolas Keriven p2268-2281 from Advances in Neural Information Processing Systems 35
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  • NOTE: Robust Continual Test-Time Adaptation Against Temporal Correlation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    NOTE: Robust Continual Test-Time Adaptation Against Temporal Correlation

    Taesik Gong, Jongheon Jeong, Taewon Kim, Yewon Kim, Jinwoo Shin, Sung-Ju Lee p27253-27266 from Advances in Neural Information Processing Systems 35
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  • Novel Object Synthesis via Adaptive Text-Image Harmony

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Novel Object Synthesis via Adaptive Text-Image Harmony

    Zeren Xiong, Zedong Zhang, Zikun Chen, Shuo Chen, Xiang Li, Gan Sun, Jian Yang, Jun Li p139085-139113 from Advances in Neural Information Processing Systems 37
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  • NOVEL TIMBER-CONCRETE COMPOSITE SLABS USING BEECH DOWELS AS CONNECTION ELEMENTS

    World Conference on Timber Engineering 2025

    NOVEL TIMBER-CONCRETE COMPOSITE SLABS USING BEECH DOWELS AS CONNECTION ELEMENTS

    Michael Mikoschek-Muggendorfer, François Colling p1361-1370 from 14th World Conference on Timber Engineering 2025 (WCTE 2025)
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