Paper

  • A Simple Approach to Automated Spectral Clustering

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Simple Approach to Automated Spectral Clustering

    Jicong Fan, Yiheng Tu, Haijun Zhang, Zhao Zhang, Mingbo Zhao p9907-9921 from Advances in Neural Information Processing Systems 35
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  • A Simple Decentralized Cross-Entropy Method

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Simple Decentralized Cross-Entropy Method

    Martin Jagersand, Jun Jin, Jun Luo, Dale Schuurmans, Zichen Zhang p36495-36506 from Advances in Neural Information Processing Systems 35
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  • A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations

    Hyesong Choi, Dongbo Min, Kwanghoon Sohn, Wonil Song p121790-121826 from Advances in Neural Information Processing Systems 37
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  • A Simple Image Segmentation Framework via In-Context Examples

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Simple Image Segmentation Framework via In-Context Examples

    Hao Chen, Chenchen Jing, Hengtao Li, Yang Liu, Chunhua Shen, Xinlong Wang, Muzhi Zhu p25095-25119 from Advances in Neural Information Processing Systems 37
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  • A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective

    Yeonsung Jung, Jin-Hwa Kim, Sung-Yub Kim, Jaeyun Song, Eunho Yang, June Yong Yang p43632-43662 from Advances in Neural Information Processing Systems 37
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  • A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories

    Alex Schwing, Yu-Xiong Wang, Kai Yan p589-623 from Advances in Neural Information Processing Systems 36
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  • A Simple Truncation Criterion in CPCs Using Constructal Theory

    ECOS 2023

    A Simple Truncation Criterion in CPCs Using Constructal Theory

    Eduardo González-Mora, Eduardo Armando Rincón-Mejía p1678-1688 from 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2023)
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  • A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm

    Yanghe Feng, Jincai Huang, Yiqin Lv, Qi Wang, Zheng Xie p12897-12928 from Advances in Neural Information Processing Systems 36
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  • A Simple yet Scalable Granger Causal Structural Learning Approach for Topological Event Sequences

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Simple yet Scalable Granger Causal Structural Learning Approach for Topological Event Sequences

    Mingjia Li, Shuo Liu, Hong Qian, Aimin Zhou p97124-97140 from Advances in Neural Information Processing Systems 37
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  • A Simple yet Universal Framework for Depth Completion

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Simple yet Universal Framework for Depth Completion

    Hae-Gon Jeon, Jin-Hwi Park p23577-23602 from Advances in Neural Information Processing Systems 37
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  • A SIMPLIFIED APPROACH FOR ESTIMATING IN-PLANE LATERAL RESPONSE OF TIMBER-FRAMED PARTITION WALLS

    World Conference on Timber Engineering 2025

    A SIMPLIFIED APPROACH FOR ESTIMATING IN-PLANE LATERAL RESPONSE OF TIMBER-FRAMED PARTITION WALLS

    Jitendra Bhatta, Joshua Mulligan, Rajesh P. Dhakal, Timothy. J Sullivan p5581-5590 from 14th World Conference on Timber Engineering 2025 (WCTE 2025)
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  • A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data

    Marko Bertogna, Nicklas Hansen, Nicola Musiu, Ayoub Raji, Adrian Remonda, Eduardo Veas, Xiaolong Wang p102078-102100 from Advances in Neural Information Processing Systems 37
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