Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization

    Zhenbo Song, Ze Xianghui, Jianfeng Lu, Yujiao Shi p70612-70625 from Advances in Neural Information Processing Systems 36
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  • Learning Dense Object Descriptors from Multiple Views for Low-Shot Category Generalization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Dense Object Descriptors from Multiple Views for Low-Shot Category Generalization

    Stefan Stojanov, Anh Thai, Zixuan Huang, James Rehg p12566-12580 from Advances in Neural Information Processing Systems 35
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  • Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation

    Zihao Yue, Anwen Hu, Liang Zhang, Qin Jin p79124-79141 from Advances in Neural Information Processing Systems 36
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  • Learning Dictionary for Visual Attention

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Dictionary for Visual Attention

    Yingjie Liu, Xuan Liu, Hui Yu, Xuan Tang, Xian Wei p56589-56601 from Advances in Neural Information Processing Systems 36
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  • Learning diffusion at lightspeed

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning diffusion at lightspeed

    Antonio Terpin, Nicolas Lanzetti, Martín Gadea, Florian Dörfler p6797-6832 from Advances in Neural Information Processing Systems 37
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  • Learning Diffusion Priors from Observations by Expectation Maximization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Diffusion Priors from Observations by Expectation Maximization

    François Rozet, Gérôme Andry, François Lanusse, Gilles Louppe p87647-87682 from Advances in Neural Information Processing Systems 37
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  • Learning Discrete Concepts in Latent Hierarchical Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Discrete Concepts in Latent Hierarchical Models

    Lingjing Kong, Guangyi Chen, Biwei Huang, Eric Xing, Yuejie Chi, Kun Zhang p36938-36975 from Advances in Neural Information Processing Systems 37
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  • Learning Discrete Latent Variable Structures with Tensor Rank Conditions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Discrete Latent Variable Structures with Tensor Rank Conditions

    Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang p17398-17427 from Advances in Neural Information Processing Systems 37
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  • Learning Disentangled Representations for Perceptual Point Cloud Quality Assessment via Mutual Information Minimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Disentangled Representations for Perceptual Point Cloud Quality Assessment via Mutual Information Minimization

    Ziyu Shan, Yujie Zhang, Yipeng Liu, Yiling Xu p84060-84080 from Advances in Neural Information Processing Systems 37
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  • Learning Distinct and Representative Modes for Image Captioning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Distinct and Representative Modes for Image Captioning

    Qi Chen, Chaorui Deng, Qi Wu p9472-9485 from Advances in Neural Information Processing Systems 35
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  • Learning Distinguishable Trajectory Representation with Contrastive Loss

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Distinguishable Trajectory Representation with Contrastive Loss

    Tianxu Li, Kun Zhu, Juan Li, Yang Zhang p64454-64478 from Advances in Neural Information Processing Systems 37
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  • Learning Distributed and Fair Policies for Network Load Balancing as Markov Potential Game

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Distributed and Fair Policies for Network Load Balancing as Markov Potential Game

    Zhiyuan Yao, Zihan Ding p28815-28828 from Advances in Neural Information Processing Systems 35
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  • Learning Distributions Generated by Single-Layer ReLU Networks in the Presence of Arbitrary Outliers

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Distributions Generated by Single-Layer ReLU Networks in the Presence of Arbitrary Outliers

    Saikiran Bulusu, Geethu Joseph, M. Cenk Gursoy, Pramod Varshney p10959-10969 from Advances in Neural Information Processing Systems 35
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  • Learning Distributions on Manifolds with Free-Form Flows

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Distributions on Manifolds with Free-Form Flows

    Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Ullrich Köthe p66961-66994 from Advances in Neural Information Processing Systems 37
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  • Learning diverse causally emergent representations from time series data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning diverse causally emergent representations from time series data

    David McSharry, Christos Kaplanis, Fernando Rosas, Pedro Mediano p119547-119572 from Advances in Neural Information Processing Systems 37
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  • Learning Domain-Aware Detection Head with Prompt Tuning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Domain-Aware Detection Head with Prompt Tuning

    Haochen Li, Rui Zhang, Hantao Yao, Xinkai Song, Yifan Hao, Yongwei Zhao, Ling Li, Yunji Chen p4248-4262 from Advances in Neural Information Processing Systems 36
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  • Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning

    Fan Feng, Sara Magliacane p19117-19144 from Advances in Neural Information Processing Systems 36
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  • Learning Dynamical Systems Via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Dynamical Systems Via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces

    Vladimir Kostic, Pietro Novelli, Andreas Maurer, Carlo Ciliberto, Lorenzo Rosasco, Massimiliano Pontil p4017-4031 from Advances in Neural Information Processing Systems 35
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  • Learning Dynamics of Deep Linear Networks with Multiple Pathways

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Dynamics of Deep Linear Networks with Multiple Pathways

    Jianghong Shi, Eric Shea-Brown, Michael Buice p34064-34076 from Advances in Neural Information Processing Systems 35
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  • Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations

    Thomas Yerxa, Yilun Kuang, Eero Simoncelli, Sueyeon Chung p24103-24128 from Advances in Neural Information Processing Systems 36
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  • Learning Efficient Surrogate Dynamic Models with Graph Spline Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Efficient Surrogate Dynamic Models with Graph Spline Networks

    Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park p52523-52547 from Advances in Neural Information Processing Systems 36
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  • Learning Efficient Vision Transformers Via Fine-Grained Manifold Distillation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Efficient Vision Transformers Via Fine-Grained Manifold Distillation

    Zhiwei Hao, Jianyuan Guo, Ding Jia, Kai Han, Yehui Tang, Chao Zhang, Han Hu, Yunhe Wang p9164-9175 from Advances in Neural Information Processing Systems 35
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  • Learning Elastic Costs to Shape Monge Displacements

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Elastic Costs to Shape Monge Displacements

    Michal Klein, Aram-Alexandre Pooladian, Pierre Ablin, Eugène Ndiaye, Jonathan Niles-Weed, Marco Cuturi p108542-108565 from Advances in Neural Information Processing Systems 37
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  • Learning Energy Networks with Generalized Fenchel-Young Losses

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Energy Networks with Generalized Fenchel-Young Losses

    Mathieu Blondel, Felipe Llinares-Lopez, Robert Dadashi, Leonard Hussenot, Matthieu Geist p12516-12528 from Advances in Neural Information Processing Systems 35
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