Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Learning from Offline Foundation Features with Tensor Augmentations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning from Offline Foundation Features with Tensor Augmentations

    Emir Konuk, Phitchapha Lertsiravaramet, Christos Matsoukas, Kevin Smith, Moein Sorkhei p120103-120123 from Advances in Neural Information Processing Systems 37
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  • Learning from Pattern Completion: Self-supervised Controllable Generation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning from Pattern Completion: Self-supervised Controllable Generation

    Zhiqiang Chen, Guofan Fan, Jinying Gao, Tiejun Huang, Bo Lei, Lei Ma, Shan Yu p27207-27235 from Advances in Neural Information Processing Systems 37
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  • Learning from Snapshots of Discrete and Continuous Data Streams

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning from Snapshots of Discrete and Continuous Data Streams

    Pramith Devulapalli, Steve Hanneke p80082-80106 from Advances in Neural Information Processing Systems 37
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  • Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate

    Tong Che, Can Jin, Yiyuan Li, Dimitris Metaxas, Marco Pavone, Hongwu Peng p966-994 from Advances in Neural Information Processing Systems 37
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  • Learning from Uncertain Data: From Possible Worlds to Possible Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning from Uncertain Data: From Possible Worlds to Possible Models

    Su Feng, Boris Glavic, Babak Salimi, Jiongli Zhu p106955-107002 from Advances in Neural Information Processing Systems 37
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  • Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm

    Vaneet Aggarwal, Qinbo Bai, Washim Mondal p108566-108599 from Advances in Neural Information Processing Systems 37
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  • Learning Generalized Linear Programming Value Functions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Generalized Linear Programming Value Functions

    Tu Anh-Nguyen, Joey Huchette, Christian Tjandraatmadja p135437-135463 from Advances in Neural Information Processing Systems 37
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  • Learning Goal-Conditioned Representations for Language Reward Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Goal-Conditioned Representations for Language Reward Models

    Jeff Da, Sean Hendryx, Yuntao Ma, Vaskar Nath, Dylan Slack, Spencer Whitehead, Hugh Zhang p117070-117108 from Advances in Neural Information Processing Systems 37
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  • Learning Group Actions on Latent Representations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Group Actions on Latent Representations

    P. Fletcher, Yinzhu Jin, Aman Shrivastava p127273-127295 from Advances in Neural Information Processing Systems 37
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  • Learning Human-like Representations to Enable Learning Human Values

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Human-like Representations to Enable Learning Human Values

    Thomas Griffiths, Ilia Sucholutsky, Andrea Wynn p30230-30260 from Advances in Neural Information Processing Systems 37
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  • Learning Identifiable Factorized Causal Representations of Cellular Responses

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Identifiable Factorized Causal Representations of Cellular Responses

    Panayiotis Benos, Jan-Christian Huetter, Kai Liu, Romain Lopez, Haiyi Mad, Lin Qiu, David Richmond p121630-121669 from Advances in Neural Information Processing Systems 37
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  • Learning Image Priors Through Patch-Based Diffusion Models for Solving Inverse Problems

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Image Priors Through Patch-Based Diffusion Models for Solving Inverse Problems

    Jeffrey Fessler, Jason Hu, Liyue Shen, Bowen Song, Xiaojian Xu p1625-1660 from Advances in Neural Information Processing Systems 37
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  • Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms

    Raman Arora, Thanh Nguyen-Tang p56268-56303 from Advances in Neural Information Processing Systems 37
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  • Learning Infinitesimal Generators of Continuous Symmetries from Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Infinitesimal Generators of Continuous Symmetries from Data

    Hyunsu Kim, Gyeonghoon Ko, Juho Lee p85973-86003 from Advances in Neural Information Processing Systems 37
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  • Learning Interaction-aware 3D Gaussian Splatting for One-shot Hand Avatars

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Interaction-aware 3D Gaussian Splatting for One-shot Hand Avatars

    Yuhao Cheng, Chengqiang Gao, Xuan Huang, Hanhui Li, Xiaodan Liang, Wanquan Liu, Yiqiang Yan p14127-14147 from Advances in Neural Information Processing Systems 37
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  • Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity

    Jikai Jin, Vasilis Syrgkanis p63466-63509 from Advances in Neural Information Processing Systems 37
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  • Learning Low-Rank Feature for Thorax Disease Classification

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Low-Rank Feature for Thorax Disease Classification

    Rajeev Goel, Utkarsh Nath, Alvin Silva, Yancheng Wang, Teresa Wu, Yingzhen Yang p117133-117163 from Advances in Neural Information Processing Systems 37
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  • Learning Macroscopic Dynamics from Partial Microscopic Observations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Macroscopic Dynamics from Partial Microscopic Observations

    Mengyi Chen, Qianxiao Li p48996-49021 from Advances in Neural Information Processing Systems 37
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  • Learning Mixtures of Unknown Causal Interventions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Mixtures of Unknown Causal Interventions

    Abhinav Kumar, Kirankumar Shiragur, Caroline Uhler p16538-16568 from Advances in Neural Information Processing Systems 37
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  • Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient

    Pulkit Agrawal, Anurag Ajay, Georgia Chalvatzaki, Tao Chen, Rickmer Krohn, Zechu Li p38456-38479 from Advances in Neural Information Processing Systems 37
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  • Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees

    Francesco Bullo, Alexander Davydov, Sean Jaffe, Deniz Lapsekili, Ambuj Singh p66204-66225 from Advances in Neural Information Processing Systems 37
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  • Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random

    Gautam Chandrasekaran, Vasilis Kontonis, Konstantinos Stavropoulos, Kevin Tian p45386-45408 from Advances in Neural Information Processing Systems 37
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  • Learning on Large Graphs using Intersecting Communities

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning on Large Graphs using Intersecting Communities

    Michael Bronstein, İsmail Ceylan, Ben Finkelshtein, Ron Levie p57349-57388 from Advances in Neural Information Processing Systems 37
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  • Learning Optimal Lattice Vector Quantizers for End-to-end Neural Image Compression

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Optimal Lattice Vector Quantizers for End-to-end Neural Image Compression

    Xiaolin Wu, Xi Zhang p106497-106518 from Advances in Neural Information Processing Systems 37
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