Paper

  • Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths

    Yuanqi Du, Berend Ensing, Lars Holdijk, Ferry Hooft, Priyank Jaini, Max Welling p79540-79556 from Advances in Neural Information Processing Systems 36
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  • Stochastic Optimal Control for Diffusion Bridges in Function Spaces

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Stochastic Optimal Control for Diffusion Bridges in Function Spaces

    Jungwon Choi, Juho Lee, Sungbin Lim, Byoungwoo Park p28745-28771 from Advances in Neural Information Processing Systems 37
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  • Stochastic Optimal Control Matching

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Stochastic Optimal Control Matching

    Brandon Amos, Joan Bruna, Ricky Chen, Carles Domingo-Enrich, Jiequn Han p112459-112504 from Advances in Neural Information Processing Systems 37
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  • Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data

    Krishnakumar Balasubramanian, Xuxing Chen, Yifan Hu, Abhishek Roy p26510-26542 from Advances in Neural Information Processing Systems 37
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  • Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss

    Qiang Li, Hoi-To Wai p8673-8697 from Advances in Neural Information Processing Systems 37
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  • Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions

    Niao He, Negar Kiyavash, Saeed Masiha, Saber Salehkaleybar, Patrick Thiran p10862-10875 from Advances in Neural Information Processing Systems 35
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  • Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators

    Zheyuan Hu, Kenji Kawaguchi, Min Lin, Zekun Shi p122316-122353 from Advances in Neural Information Processing Systems 37
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  • Stochastic Window Transformer for Image Restoration

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Stochastic Window Transformer for Image Restoration

    Xueyang Fu, Feng Wu, Jie Xiao, Zheng-Jun Zha p9315-9329 from Advances in Neural Information Processing Systems 35
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  • Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity

    Baihe Huang, Jason Lee, Qi Lei, Yining Wang, Qian Yu p99564-99600 from Advances in Neural Information Processing Systems 37
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  • STONE: A Submodular Optimization Framework for Active 3D Object Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    STONE: A Submodular Optimization Framework for Active 3D Object Detection

    Yunhui Guo, Rishabh Iyer, Sarthak Maharana, Ruiyu Mao p48292-48308 from Advances in Neural Information Processing Systems 37
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  • Stopping Bayesian Optimization with Probabilistic Regret Bounds

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Stopping Bayesian Optimization with Probabilistic Regret Bounds

    James Wilson p98264-98296 from Advances in Neural Information Processing Systems 37
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  • STORM: Efficient Stochastic Transformer based World Models for Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    STORM: Efficient Stochastic Transformer based World Models for Reinforcement Learning

    Gao Huang, Jian Sun, Gang Wang, Yetian Yuan, Weipu Zhang p27147-27166 from Advances in Neural Information Processing Systems 36
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