Machine Learning Methods for Studying Latent Neural Activity Dynamics
研究潜在神经活动动力学的机器学习方法
Shufeng Kong, Fumei Deng, Xinyi Dong, Caihua Liu, Weiwei Chen, Yingheng Wang, Daniel Cao, Azahara Oliva, Antonio Fernandez-Ruiz, Carla Gomes
机构
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School of Software Engineering, Sun Yat-sen University(中山大学软件工程学院)
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Department of Computer Science, Cornell University(康奈尔大学计算机科学系)
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Department of Neurobiology and Behavior, Cornell University(康奈尔大学神经生物学与行为学系)
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Department of Ecology and Evolutionary Biology, Cornell University(康奈尔大学生态学与进化生物学系)
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School of Computer Science and Artificial Intelligence, Foshan University(佛山大学计算机科学与人工智能学院)
CommentsAn edited version of this paper was published by AGU. Published 2026 American Geophysical Union. For supplementary materials please contact the authors. Citation will be added
Self-Consistent Generative Paths via Admissible Random Variational Transport
通过可容许随机变分输运的自洽生成路径
Lei Luo, Yingzhen Zhang, Jian Yang
机构
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PCA Lab, Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, School of Computer Science and Engineering, Nanjing University of Science and Technology(南京理工大学计算机科学与工程学院高维信息智能感知与系统教育部重点实验室PCA实验室)