Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Towards Theoretically Inspired Neural Initialization Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Theoretically Inspired Neural Initialization Optimization

    Yibo Yang, Hong Wang, Haobo Yuan, Zhouchen Lin p18983-18995 from Advances in Neural Information Processing Systems 35
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  • Towards training digitally-tied analog blocks via hybrid gradient computation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards training digitally-tied analog blocks via hybrid gradient computation

    Timothy Nest, Maxence Ernoult p83877-83914 from Advances in Neural Information Processing Systems 37
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  • Towards Trustworthy Automatic Diagnosis Systems by Emulating Doctors' Reasoning with Deep Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Trustworthy Automatic Diagnosis Systems by Emulating Doctors' Reasoning with Deep Reinforcement Learning

    Arsene Fansi Tchango, Rishab Goel, Julien Martel, Zhi Wen, Gaetan Marceau Caron, Joumana Ghosn p24502-24515 from Advances in Neural Information Processing Systems 35
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  • Towards Unbounded Machine Unlearning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Unbounded Machine Unlearning

    Meghdad Kurmanji, Peter Triantafillou, Jamie Hayes, Eleni Triantafillou p1957-1987 from Advances in Neural Information Processing Systems 36
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  • Towards Understanding Evolving Patterns in Sequential Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Understanding Evolving Patterns in Sequential Data

    Qiuhao Zeng, Long-Kai Huang, Qi Chen, Charles Ling, Boyu Wang p132747-132773 from Advances in Neural Information Processing Systems 37
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  • Towards Understanding Extrapolation: a Causal Lens

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Understanding Extrapolation: a Causal Lens

    Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric Xing, Kun Zhang p123534-123562 from Advances in Neural Information Processing Systems 37
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  • Towards Understanding Grokking: An Effective Theory of Representation Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Understanding Grokking: An Effective Theory of Representation Learning

    Ziming Liu, Ouail Kitouni, Niklas S Nolte, Eric Michaud, Max Tegmark, Mike Williams p34651-34663 from Advances in Neural Information Processing Systems 35
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  • Towards Understanding How Transformers Learn In-context Through a Representation Learning Lens

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Understanding How Transformers Learn In-context Through a Representation Learning Lens

    Ruifeng Ren, Yong Liu p892-933 from Advances in Neural Information Processing Systems 37
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  • Towards Understanding the Condensation of Neural Networks at Initial Training

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Understanding the Condensation of Neural Networks at Initial Training

    Hanxu Zhou, Zhou Qixuan, Tao Luo, Yaoyu Zhang, Zhi-Qin Xu p2184-2196 from Advances in Neural Information Processing Systems 35
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  • Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent

    Tianle Liu, Promit Ghosal, Krishnakumar Balasubramanian, Natesh Pillai p61234-61291 from Advances in Neural Information Processing Systems 36
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  • Towards Understanding the Mixture-Of-Experts Layer in Deep Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Understanding the Mixture-Of-Experts Layer in Deep Learning

    Zixiang Chen, Yihe Deng, Yue Wu, Quanquan Gu, Yuanzhi Li p23049-23062 from Advances in Neural Information Processing Systems 35
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  • Towards Understanding the Working Mechanism of Text-to-Image Diffusion Model

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Understanding the Working Mechanism of Text-to-Image Diffusion Model

    Mingyang Yi, Aoxue Li, Yi Xin, Zhenguo Li p55342-55369 from Advances in Neural Information Processing Systems 37
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  • Towards Unified Multimodal Editing with Enhanced Knowledge Collaboration

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Unified Multimodal Editing with Enhanced Knowledge Collaboration

    Kaihang Pan, Zhaoyu Fan, Juncheng Li, Qifan Yu, Hao Fei, Siliang Tang, Richang Hong, Hanwang Zhang, Qianru Sun p110290-110314 from Advances in Neural Information Processing Systems 37
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  • Towards Universal Mesh Movement Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Universal Mesh Movement Networks

    Mingrui Zhang, Chunyang Wang, Stephan Kramer, Joseph Wallwork, Siyi Li, Jiancheng Liu, Xiang Chen, Matthew Piggott p14934-14961 from Advances in Neural Information Processing Systems 37
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  • Towards Unsupervised Model Selection for Domain Adaptive Object Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Unsupervised Model Selection for Domain Adaptive Object Detection

    Hengfu Yu, Jinhong Deng, Wen Li, Lixin Duan p58423-58444 from Advances in Neural Information Processing Systems 37
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  • Towards Versatile Embodied Navigation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Versatile Embodied Navigation

    Hanqing Wang, Wei Liang, Luc V Gool, Wenguan Wang p36858-36874 from Advances in Neural Information Processing Systems 35
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  • Towards Video Text Visual Question Answering: Benchmark and Baseline

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Video Text Visual Question Answering: Benchmark and Baseline

    Minyi Zhao, Bingjia Li, Jie Wang, Wanqing Li, Wenjing Zhou, Lan Zhang, Shijie Xuyang, Zhihang Yu, Xinkun Yu, Guangze Li, Aobotao Dai, Shuigeng Zhou p35549-35562 from Advances in Neural Information Processing Systems 35
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  • Towards Visual Text Design Transfer Across Languages

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Towards Visual Text Design Transfer Across Languages

    Yejin Choi, Jiwan Chung, Sumin Shim, Giyeong Oh, Youngjae Yu p89706-89727 from Advances in Neural Information Processing Systems 37
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  • Toxicity Detection for Free

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Toxicity Detection for Free

    Zhanhao Hu, Julien Piet, Geng Zhao, Jiantao Jiao, David Wagner p17518-17540 from Advances in Neural Information Processing Systems 37
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  • TPC: Test-time Procrustes Calibration for Diffusion-based Human Image Animation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    TPC: Test-time Procrustes Calibration for Diffusion-based Human Image Animation

    Sunjae Yoon, Gwanhyeong Koo, Younghwan Lee, Chang Yoo p118654-118677 from Advances in Neural Information Processing Systems 37
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  • TPR: Topology-Preserving Reservoirs for Generalized Zero-Shot Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    TPR: Topology-Preserving Reservoirs for Generalized Zero-Shot Learning

    Hui Chen, Yanbin Liu, Yongqiang Ma, Nanning Zheng, Xin Yu p102229-102254 from Advances in Neural Information Processing Systems 37
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  • TPU-KNN: K Nearest Neighbor Search at Peak FLOP/s

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    TPU-KNN: K Nearest Neighbor Search at Peak FLOP/s

    Felix Chern, Blake Hechtman, Andy Davis, Ruiqi Guo, David Majnemer, Sanjiv Kumar p15489-15501 from Advances in Neural Information Processing Systems 35
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  • TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs

    Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Michael Burrows, Charith Mendis, Bryan Perozzi p70355-70375 from Advances in Neural Information Processing Systems 36
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  • Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

    Ching-An Cheng, Allen Nie, Adith Swaminathan p71596-71642 from Advances in Neural Information Processing Systems 37
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