Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding

    Lunhao Duan, Shanshan Zhao, Nan Xue, Mingming Gong, Gui-Song Xia, Dacheng Tao p23886-23901 from Advances in Neural Information Processing Systems 36
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  • Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference

    Tao Lei, Junwen Bai, Siddhartha Brahma, Joshua Ainslie, Kenton Lee, Yanqi Zhou, Nan Du, Vincent Zhao, Yuexin Wu, Bo Li, Yu Zhang, Ming-Wei Chang p8152-8172 from Advances in Neural Information Processing Systems 36
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  • Conditional Controllable Image Fusion

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Controllable Image Fusion

    Bing Cao, Xingxin Xu, Pengfei Zhu, Qilong Wang, Qinghua Hu p120311-120335 from Advances in Neural Information Processing Systems 37
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  • Conditional Density Estimation with Histogram Trees

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Density Estimation with Histogram Trees

    Lincen Yang, Matthijs Van Leeuwen p117315-117339 from Advances in Neural Information Processing Systems 37
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  • Conditional Diffusion Anomaly Modeling on Graphs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Diffusion Anomaly Modeling on Graphs

    Chunyu Wei, Haozhe Lin, Yueguo Chen, Yunhai Wang p170320-170356 from Advances in Neural Information Processing Systems 38
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  • Conditional Diffusion Process for Inverse Halftoning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Diffusion Process for Inverse Halftoning

    Hao Jiang, Yadong Mu p5498-5509 from Advances in Neural Information Processing Systems 35
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  • Conditional Distribution Compression via the Kernel Conditional Mean Embedding

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Distribution Compression via the Kernel Conditional Mean Embedding

    Dominic Broadbent, Nick Whiteley, Robert Allison, Tom Lovett p88468-88543 from Advances in Neural Information Processing Systems 38
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  • Conditional Forecasts and Proper Scoring Rules for Reliable and Accurate Performative Predictions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Forecasts and Proper Scoring Rules for Reliable and Accurate Performative Predictions

    Philip Boeken, Onno Zoeter, Joris Mooij p18265-18298 from Advances in Neural Information Processing Systems 38
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  • Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand

    Md Musfiqur Rahman, Matt Jordan, Murat Kocaoglu p77269-77315 from Advances in Neural Information Processing Systems 37
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  • Conditional Gradient Methods with Standard LMO for Stochastic Simple Bilevel Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Gradient Methods with Standard LMO for Stochastic Simple Bilevel Optimization

    Khanh-Hung (Bruce) Giang-Tran, Soroosh Shafiee, Nam Ho-Nguyen p104220-104265 from Advances in Neural Information Processing Systems 38
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  • Conditional independence testing under misspecified inductive biases

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional independence testing under misspecified inductive biases

    Felipe Maia Polo, Yuekai Sun, Moulinath Banerjee p58577-58612 from Advances in Neural Information Processing Systems 36
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  • Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery

    Wiebke Günther, Urmi Ninad, Jonas Wahl, Jakob Runge p16191-16202 from Advances in Neural Information Processing Systems 35
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  • Conditional Matrix Flows for Gaussian Graphical Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Matrix Flows for Gaussian Graphical Models

    Marcello Massimo Negri, Fabricio Arend Torres, Volker Roth p25095-25111 from Advances in Neural Information Processing Systems 36
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  • Conditional Meta-Learning of Linear Representations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Meta-Learning of Linear Representations

    Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto p253-266 from Advances in Neural Information Processing Systems 35
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  • Conditional Mutual Information for Disentangled Representations in Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Mutual Information for Disentangled Representations in Reinforcement Learning

    Mhairi Dunion, Trevor McInroe, Kevin Luck, Josiah Hanna, Stefano Albrecht p80111-80129 from Advances in Neural Information Processing Systems 36
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  • Conditional Outcome Equivalence: A Quantile Alternative to CATE

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Outcome Equivalence: A Quantile Alternative to CATE

    Josh Givens, Henry Reeve, Song Liu, Katarzyna Reluga p102634-102671 from Advances in Neural Information Processing Systems 37
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  • Conditional Panoramic Image Generation via Masked Autoregressive Modeling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Panoramic Image Generation via Masked Autoregressive Modeling

    Chaoyang Wang, Xiangtai Li, Lu Qi, Xiaofan Lin, Jinbin Bai, Qianyu Zhou, Yunhai Tong p31432-31457 from Advances in Neural Information Processing Systems 38
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  • Conditional Representation Learning for Customized Tasks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Representation Learning for Customized Tasks

    Honglin Liu, Chao Sun, Peng Hu, Yunfan Li, Xi Peng p35774-35805 from Advances in Neural Information Processing Systems 38
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  • Conditional Score Guidance for Text-Driven Image-to-Image Translation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Score Guidance for Text-Driven Image-to-Image Translation

    Hyunsoo Lee, Minsoo Kang, Bohyung Han p38685-38708 from Advances in Neural Information Processing Systems 36
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  • Conditional score-based diffusion models for Bayesian inference in infinite dimensions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional score-based diffusion models for Bayesian inference in infinite dimensions

    Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. De Hoop p24262-24290 from Advances in Neural Information Processing Systems 36
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  • Conditional Synthesis of 3D Molecules with Time Correction Sampler

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditional Synthesis of 3D Molecules with Time Correction Sampler

    Hojung Jung, Youngrok Park, Laura Schmid, Jaehyeong Jo, Dongkyu Lee, Bongsang Kim, Se-Young Yun, Jinwoo Shin p75914-75941 from Advances in Neural Information Processing Systems 37
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  • Conditioning Matters: Training Diffusion Policies is Faster Than You Think

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditioning Matters: Training Diffusion Policies is Faster Than You Think

    Zibin Dong, Yicheng Liu, Yinchuan Li, Hang Zhao, Jianye Hao p132661-132686 from Advances in Neural Information Processing Systems 38
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  • Conditioning non-linear and infinite-dimensional diffusion processes

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Conditioning non-linear and infinite-dimensional diffusion processes

    Elizabeth Baker, Gefan Yang, Michael Severinsen, Christy Hipsley, Stefan Sommer p10801-10826 from Advances in Neural Information Processing Systems 37
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  • CondTSF: One-line Plugin of Dataset Condensation for Time Series Forecasting

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    CondTSF: One-line Plugin of Dataset Condensation for Time Series Forecasting

    Jianrong Ding, Zhanyu Liu, Guanjie Zheng, Haiming Jin, Linghe Kong p128227-128259 from Advances in Neural Information Processing Systems 37
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