Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients

    Sima Behpour, Thang Long Doan, Xin Li, Wenbin He, Liang Gou, Liu Ren p38206-38230 from Advances in Neural Information Processing Systems 36
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  • Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization

    Amirhossein Saberi, Amir Najafi, Amin Behjati, Ala Emrani, Yasaman Zolfit, Mahdi Shadrooy, Abolfazl Motahari, Babak Khalaj p73693-73725 from Advances in Neural Information Processing Systems 37
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  • Grammar Prompting for Domain-Specific Language Generation with Large Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Grammar Prompting for Domain-Specific Language Generation with Large Language Models

    Bailin Wang, Zi Wang, Xuezhi Wang, Yuan Cao, Rif A. Saurous, Yoon Kim p65030-65055 from Advances in Neural Information Processing Systems 36
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  • Grammar-Aligned Decoding

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Grammar-Aligned Decoding

    Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick, Nadia Polikarpova, Loris D'Antoni p24547-24568 from Advances in Neural Information Processing Systems 37
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  • GRAND-SLAMIN’ Interpretable Additive Modeling with Structural Constraints

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    GRAND-SLAMIN’ Interpretable Additive Modeling with Structural Constraints

    Shibal Ibrahim, Gabriel Afriat, Kayhan Behdin, Rahul Mazumder p61158-61186 from Advances in Neural Information Processing Systems 36
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  • Granger Components Analysis: Unsupervised learning of latent temporal dependencies

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Granger Components Analysis: Unsupervised learning of latent temporal dependencies

    Jacek Dmochowski p78168-78180 from Advances in Neural Information Processing Systems 36
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  • GRANOLA: Adaptive Normalization for Graph Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    GRANOLA: Adaptive Normalization for Graph Neural Networks

    Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron p90514-90551 from Advances in Neural Information Processing Systems 37
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  • Graph Classification via Reference Distribution Learning: Theory and Practice

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Classification via Reference Distribution Learning: Theory and Practice

    Zixiao Wang, Jicong Fan p137698-137740 from Advances in Neural Information Processing Systems 37
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  • Graph Coarsening with Message-Passing Guarantees

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Coarsening with Message-Passing Guarantees

    Antonin Joly, Nicolas Keriven p114902-114927 from Advances in Neural Information Processing Systems 37
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  • Graph Coloring Via Neural Networks for Haplotype Assembly and Viral Quasispecies Reconstruction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Coloring Via Neural Networks for Haplotype Assembly and Viral Quasispecies Reconstruction

    Hansheng Xue, Vaibhav Rajan, Yu Lin p30898-30910 from Advances in Neural Information Processing Systems 35
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  • Graph Contrastive Learning with Stable and Scalable Spectral Encoding

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Contrastive Learning with Stable and Scalable Spectral Encoding

    Deyu Bo, Yuan Fang, Yang Liu, Chuan Shi p45516-45532 from Advances in Neural Information Processing Systems 36
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  • Graph Convolution Network Based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Convolution Network Based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy

    Leyan Deng, Defu Lian, Chenwang Wu, Enhong Chen p3900-3912 from Advances in Neural Information Processing Systems 35
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  • Graph Convolutional Kernel Machine versus Graph Convolutional Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Convolutional Kernel Machine versus Graph Convolutional Networks

    Zhihao Wu, Zhao Zhang, Jicong Fan p19650-19672 from Advances in Neural Information Processing Systems 36
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  • Graph Convolutions Enrich the Self-Attention in Transformers!

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Convolutions Enrich the Self-Attention in Transformers!

    Jeongwhan Choi, Hyowon Wi, Jayoung Kim, Yehjin Shin, Kookjin Lee, Nathaniel Trask, Noseong Park p52891-52936 from Advances in Neural Information Processing Systems 37
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  • Graph Denoising Diffusion for Inverse Protein Folding

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Denoising Diffusion for Inverse Protein Folding

    Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Lió, Yuguang Wang p10238-10257 from Advances in Neural Information Processing Systems 36
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  • Graph Diffusion Policy Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Diffusion Policy Optimization

    Yijing Liu, Chao Du, Tianyu Pang, Chongxuan Li, Min Lin, Wei Chen p9585-9611 from Advances in Neural Information Processing Systems 37
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  • Graph Diffusion Transformers for Multi-Conditional Molecular Generation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Diffusion Transformers for Multi-Conditional Molecular Generation

    Gang Liu, Jiaxin Xu, Tengfei Luo, Meng Jiang p8065-8092 from Advances in Neural Information Processing Systems 37
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  • Graph Edit Distance with General Costs Using Neural Set Divergence

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Edit Distance with General Costs Using Neural Set Divergence

    Eeshaan Jain, Indradyumna Roy, Saswat Meher, Soumen Chakrabarti, Abir De p73399-73438 from Advances in Neural Information Processing Systems 37
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  • Graph Few-Shot Learning with Task-Specific Structures

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Few-Shot Learning with Task-Specific Structures

    Song Wang, Chen Chen, Jundong Li p38925-38936 from Advances in Neural Information Processing Systems 35
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  • Graph Learning Assisted Multi-Objective Integer Programming

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Learning Assisted Multi-Objective Integer Programming

    Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Abhishek Gupta, Mingyan Lin p17774-17787 from Advances in Neural Information Processing Systems 35
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  • Graph Learning for Numeric Planning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Learning for Numeric Planning

    Dillon Chen, Sylvie Thiébaux p91156-91183 from Advances in Neural Information Processing Systems 37
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  • Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling

    Haotao Wang, Ziyu Jiang, Yuning You, Yan Han, Gaowen Liu, Jayanth Srinivasa, Ramana Kompella, Zhangyang "atlas" Wang p50825-50837 from Advances in Neural Information Processing Systems 36
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  • Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series

    Giangiacomo Mercatali, Andre Freitas, Jie Chen p57183-57206 from Advances in Neural Information Processing Systems 37
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  • Graph Neural Network Bandits

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Graph Neural Network Bandits

    Parnian Kassraie, Andreas Krause, Ilija Bogunovic p34519-34531 from Advances in Neural Information Processing Systems 35
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