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  • Divergences between Language Models and Human Brains

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Divergences between Language Models and Human Brains

    Emmy Liu, Graham Neubig, Michael Tarr, Leila Wehbe, Yuchen Zhou p137999-138031 from Advances in Neural Information Processing Systems 37
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  • Diverse Forage Brassica Genotypes Have Potential to Augment Forage Supply on Drier Mixed Crop-Livestock Farms Across Australia

    International Grassland Congress 2023

    Diverse Forage Brassica Genotypes Have Potential to Augment Forage Supply on Drier Mixed Crop-Livestock Farms Across Australia

    L. W. Bell, L. J. Watt, R. Stutz p1049-1052 from XXV International Grassland Congress (IGC 2023)
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  • Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec

    Jun-Hyuk Kim, Seungeon Kim, Won-Hee Lee, Dokwan Oh p45956-45974 from Advances in Neural Information Processing Systems 37
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  • Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners

    Rujikorn Charakorn, Nat Dilokthanakul, Poramate Manoonpong p56401-56423 from Advances in Neural Information Processing Systems 37
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  • Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment

    Jiawei Du, Juncheng Hu, Wenxing Huang, Xin Zhang, Joey Zhou p119443-119465 from Advances in Neural Information Processing Systems 37
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  • Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation

    Jingchang Chen, Qianglong Chen, Zheng Chu, Ming Liu, Bing Qin, Hongxuan Tang, Zekun Wang p67061-67105 from Advances in Neural Information Processing Systems 37
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  • Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors

    Alain Durmus, Yazid Janati, Badr Moufad, Eric Moulines, Jimmy Olsson p97408-97444 from Advances in Neural Information Processing Systems 37
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  • Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm

    Tommaso Salvatori, Eli Sennesh, Hao Wu p48599-48627 from Advances in Neural Information Processing Systems 37
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  • Division of Aquifer Groups and Their Permeability Analysis in a Livestock Farm Survey Area

    Aussino Academic Publishing House (AAPH)

    Division of Aquifer Groups and Their Permeability Analysis in a Livestock Farm Survey Area

    Xueqiong Zhao, Bo Song, Zhenghong Yang, Qinhui Huang p974-978 from 11th Academic Conference of Geology Resource Management and Sustainable Development 2023
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  • DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors

    Antoine Dedieu, J. Guntupalli, Ahmad Humayun, Miguel Lázaro-Gredilla, Wolfgang Lehrach, Kevin Murphy, Joseph Ortiz, Sivaramakrishnan Swaminathan, Carter Wendelken, Guangyao Zhou p6574-6602 from Advances in Neural Information Processing Systems 37
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  • DMesh: A Differentiable Mesh Representation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DMesh: A Differentiable Mesh Representation

    Matheus Gadelha, Ming Lin, Sanghyun Son, Zexiang Xu, Yang Zhou, Yi Zhou p12035-12077 from Advances in Neural Information Processing Systems 37
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  • DMNet: Self-comparison Driven Model for Subject-independent Seizure Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DMNet: Self-comparison Driven Model for Subject-independent Seizure Detection

    Linfeng Cao, Junru Chen, Lvbin Ma, Shihao Tu, Yang Yang, Daoze Zhang, Yin Zhang p28254-28280 from Advances in Neural Information Processing Systems 37
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