Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Understanding Model Selection for Learning in Strategic Environments

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding Model Selection for Learning in Strategic Environments

    Tinashe Handina, Eric Mazumdar p92952-92982 from Advances in Neural Information Processing Systems 37
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  • Understanding Multi-Granularity for Open-Vocabulary Part Segmentation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding Multi-Granularity for Open-Vocabulary Part Segmentation

    Jiho Choi, Minhyun Lee, Seonho Lee, Seungho Lee, Hyunjung Shim p137161-137189 from Advances in Neural Information Processing Systems 37
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  • Understanding Multi-phase Optimization Dynamics and Rich Nonlinear Behaviors of ReLU Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding Multi-phase Optimization Dynamics and Rich Nonlinear Behaviors of ReLU Networks

    Chao Ma, Mingze Wang p35654-35747 from Advances in Neural Information Processing Systems 36
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  • Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers

    Xinlin Li, Yiwei Lu, Vahid Partovi Nia, Yaoliang Yu p40468-40486 from Advances in Neural Information Processing Systems 36
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  • Understanding Non-Linearity in Graph Neural Networks from the Bayesian-Inference Perspective

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding Non-Linearity in Graph Neural Networks from the Bayesian-Inference Perspective

    Austin Benson, Junteng Jia, Pan Li, Rongzhe Wei, Haoteng Yin p34024-34038 from Advances in Neural Information Processing Systems 35
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  • Understanding Programmatic Weak Supervision Via Source-Aware Influence Function

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding Programmatic Weak Supervision Via Source-Aware Influence Function

    Cheng-Yu Hsieh, Alexander Ratner, Haonan Wang, Jieyu Zhang p2862-2875 from Advances in Neural Information Processing Systems 35
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  • Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective

    Ye Shi, Haixiang Sun p9634-9667 from Advances in Neural Information Processing Systems 37
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  • Understanding Robust Learning Through the Lens of Representation Similarities

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding Robust Learning Through the Lens of Representation Similarities

    Arjun Nitin Bhagoji, Christian Cianfarani, Prateek Mittal, Vikash Sehwag, Ben Zhao, Heather Zheng p34912-34925 from Advances in Neural Information Processing Systems 35
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  • Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data

    Alex Havrilla, Wenjing Liao p42162-42210 from Advances in Neural Information Processing Systems 37
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  • Understanding Social Reasoning in Language Models with Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding Social Reasoning in Language Models with Language Models

    Jan-Philipp Fraenken, Kanishk Gandhi, Tobias Gerstenberg, Noah Goodman p13518-13529 from Advances in Neural Information Processing Systems 36
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  • Understanding Square Loss in Training Overparametrized Neural Network Classifiers

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding Square Loss in Training Overparametrized Neural Network Classifiers

    Tianyang Hu, Zhenguo Li, Wenjia Wang, Jun Wang p16495-16508 from Advances in Neural Information Processing Systems 35
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  • Understanding the detrimental class-level effects of data augmentation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the detrimental class-level effects of data augmentation

    Randall Balestriero, Diane Bouchacourt, Hamed Firooz, Mark Ibrahim, Polina Kirichenko, Shanmukha Ramakrishna Vedantam, Andrew Wilson p17498-17526 from Advances in Neural Information Processing Systems 36
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  • Understanding the Differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks

    Carmen Alonso, Alexandre Didier, Antonio Orvieto, Jerome Sieber, Melanie Zeilinger p134534-134566 from Advances in Neural Information Processing Systems 37
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  • Understanding the Eluder Dimension

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Eluder Dimension

    Dylan J Foster, Pritish Kamath, Gene Li, Nati Srebro p23737-23750 from Advances in Neural Information Processing Systems 35
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  • Understanding the Evolution of Linear Regions in Deep Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Evolution of Linear Regions in Deep Reinforcement Learning

    Setareh Cohan, Nam Hee Kim, David Rolnick, Michiel Van De Panne p10891-10903 from Advances in Neural Information Processing Systems 35
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  • Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling

    Weinan E, Mingze Wang p25781-25856 from Advances in Neural Information Processing Systems 37
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  • Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective

    Masahiro Fujisawa, Takeshi Koshizuka, Issei Sato, Yusuke Tanaka p11021-11060 from Advances in Neural Information Processing Systems 37
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  • Understanding the Failure of Batch Normalization for Transformers in NLP

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Failure of Batch Normalization for Transformers in NLP

    Lei Huang, Jiaxi Wang, Ji Wu p37617-37630 from Advances in Neural Information Processing Systems 35
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  • Understanding the Gains from Repeated Self-Distillation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Gains from Repeated Self-Distillation

    Simon Du, Sewoong Oh, Divyansh Pareek p7759-7796 from Advances in Neural Information Processing Systems 37
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  • Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction

    Sanjeev Arora, Zhiyuan Li, Kaifeng Lyu p34689-34708 from Advances in Neural Information Processing Systems 35
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  • Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry

    Jaewoong Choi, Junghyo Jo, Mingi Kwon, Yong-Hyun Park, Youngjung Uh p24129-24142 from Advances in Neural Information Processing Systems 36
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  • Understanding the Limitations of Deep Models for Molecular property prediction: Insights and Solutions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Limitations of Deep Models for Molecular property prediction: Insights and Solutions

    Zhangyang Gao, Bozhen Hu, Siyuan Li, Stan Z. Li, Yue Liu, Cheng Tan, Jun Xia, Lecheng Zhang, Jiangbin Zheng, Xiao Zhu p64774-64792 from Advances in Neural Information Processing Systems 36
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  • Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem

    Declan Campbell, Jonathan Cohen, Nicolò De Sabbata, Steven Frankland, Kia Ghods, Tyler Giallanza, Thomas Griffiths, Amogh Joshi, Alexander Ku, Sunayana Rane, Taylor Webb p113436-113460 from Advances in Neural Information Processing Systems 37
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  • Understanding the Role of Equivariance in Self-supervised Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Understanding the Role of Equivariance in Self-supervised Learning

    Yisen Wang, Sharut Gupta, Kaiwen Hu, Stefanie Jegelka, Yifei Wang, Ziyu Ye p127483-127510 from Advances in Neural Information Processing Systems 37
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