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Stochastic Process Learning via Operator Flow Matching

• Authors : Shi, Yaozhong; Ross, Zachary E.; Asimaki, Domniki

Subjects: Computer Science - Machine Learning

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From Target Tracking to Targeting Track -- Part III: Stochastic Process Modeling and Online Learning

• Authors : Li, Tiancheng; Wang, Jingyuan; Li, Guchong

Subjects: Electrical Engineering and Systems Science - Systems and Control; Electrical Engineering and Systems Science - Signal Processing; Statistics - Machine Learning

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A stochastic process defined via the random permutation divisors

• Authors : Manstavičius, Eugenijus

Subjects: Mathematics - Probability; 60F17, 60C05

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Efficient measure of information backflow with quasi-stochastic process

• Authors : Onggadinata, Kelvin; Koh, Teck Seng

Subjects: Quantum Physics

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A Stochastic Process-Based Approach for Power System Modeling and Simulation: A Case Study on China's Long-Term Coal-Fired Power Phaseout.

• Authors : Yang, Rui^1,2 (AUTHOR); Wang, Wensheng^1,2 (AUTHOR); Chang, Chuangye³ (AUTHOR)

• Source: Sustainability (2071-1050). Mar2025, Vol. 17 Issue 5, p2303. 23p.

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Stochastic Process Turing Machines

• Authors : Wolpert, David; Scharnhorst, Jordan

Subjects: Computer Science - Computational Complexity; Computer Science - Formal Languages and Automata Theory; Computer Science - Logic in Computer Science

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Synchronization of two bacterial flagella as a stochastic process

• Authors : Qin, Jing; Uchida, Nariya

Subjects: Nonlinear Sciences - Adaptation and Self-Organizing Systems; Physics - Biological Physics

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Stochastic process model for interfacial gap of purely normal elastic rough surface contact

• Authors : Xu, Yang; Joe, Junki; Li, Xiaobao

Subjects: Condensed Matter - Soft Condensed Matter

• Source: Journal of the Mechanics and Physics of Solids, 2024, 105823

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An operator theory approach to the evanescent part of a two-parametric weak-stationary stochastic process

• Authors : Burdak, Zbigniew; Kosiek, Marek; Pagacz, Patryk

Subjects: Mathematics - Probability; Mathematics - Functional Analysis; 47B20, 47A13, 60G10, 60G25

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HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models

• Authors : Meng, Tingwei; Zou, Zongren; Darbon, Jérôme

Subjects: Computer Science - Machine Learning; Mathematics - Optimization and Control; Statistics - Computation

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