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检索条件"机构=Graduate Program in Dynamical Neuroscience"
15 条 记 录,以下是1-10 订阅
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Simulated prosthetic vision identifies checkerboard as an effective raster pattern for retinal implants
arXiv
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arXiv 2025年
作者: Kasowski, Justin M. Beyeler, Michael Interdepartmental Graduate Program in Dynamical Neuroscience University of California Santa BarbaraCA93106 United States Department of Computer Science University of California Santa BarbaraCA93106 United States Department of Psychological & Brain Sciences University of California Santa BarbaraCA93106 United States
Objective: This study systematically evaluates the impact of raster patterns-specific spatial arrangements of sequential electrode activation-on performance and perceived difficulty in simulated prosthetic vision (SPV... 详细信息
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Renormalization group as a Koopman operator
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Physical Review E 2020年 第6期101卷 060104(R)-060104(R)页
作者: William T. Redman Interdepartmental Graduate Program in Dynamical Neuroscience University of California Santa Barbara California 93106 USA
Koopman operator theory is shown to be directly related to the renormalization group. This observation allows us, with no assumption of translational invariance, to compute the critical exponents η and δ, as well as... 详细信息
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The estrous cycle modulates hippocampal spine dynamics, dendritic processing, and spatial coding
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Neuron 2025年
作者: Wolcott, Nora S. Redman, William T. Karpinska, Marie Jacobs, Emily G. Goard, Michael J. Department of Molecular Cellular and Developmental Biology University of California Santa Barbara Santa Barbara 93106 CA United States Interdepartmental Graduate Program in Dynamical Neuroscience University of California Santa Barbara Santa Barbara 93106 CA United States Intelligent Systems Center Johns Hopkins University Applied Physics Laboratory Laurel 20723 MD United States Department of Computer Science University of California Santa Barbara Santa Barbara 93106 CA United States Department of Psychological & Brain Sciences University of California Santa Barbara Santa Barbara 93106 CA United States Ann S. Bowers Women's Brain Health Initiative University of California Santa Barbara Santa Barbara 93106 CA United States Neuroscience Research Institute University of California Santa Barbara Santa Barbara 93106 CA United States
Histological evidence suggests that the estrous cycle exerts a powerful influence on CA1 neurons in the mammalian hippocampus. Decades have passed since this landmark observation, yet how the estrous cycle shapes dend... 详细信息
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Modulation of Dopamine for Adaptive Learning: a Neurocomputational Model
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Computational Brain and Behavior 2021年 第1期4卷 34-52页
作者: Inglis, Jeffrey B. Valentin, Vivian V. Ashby, F. Gregory Interdepartmental Graduate Program in Dynamical Neuroscience University of California Santa Barbara 93106 CA United States Department of Psychological & Brain Sciences University of California Santa Barbara 93106 CA United States
There have been many proposals that learning rates in the brain are adaptive, in the sense that they increase or decrease depending on environmental conditions. The majority of these models are abstract and make no at... 详细信息
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On Koopman mode decomposition and tensor component analysis
arXiv
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arXiv 2021年
作者: Redman, William T. Interdepartmental Graduate Program in Dynamical Neuroscience University of California Santa Barbara CA93106 United States
Koopman mode decomposition and tensor component analysis (also known as CANDECOMP/PARAFAC or canonical polyadic decomposition) are two popular approaches of decomposing high dimensional data sets into modes that captu... 详细信息
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Control of ecological outcomes through deliberate parameter changes in a model of the gut microbiome
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Physical Review E 2020年 第5期101卷 052402-052402页
作者: Zipeng Wang Eric W. Jones Joshua M. Mueller Jean M. Carlson Department of Physics University of California Santa Barbara Santa Barbara California 93106 USA Interdepartmental Graduate Program in Dynamical Neuroscience University of California Santa Barbara Santa Barbara California 93106 USA
The generalized Lotka-Volterra (gLV) equations are a mathematical proxy for ecological dynamics. We focus on a gLV model of the gut microbiome, in which the evolution of the gut microbial state is determined in part b... 详细信息
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Learning Linear Embeddings for Non-Linear Network Dynamics with Koopman Message Passing
arXiv
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arXiv 2023年
作者: Yeh, King Fai Flood, Paris Redman, William Liò, Pietro Department of Computer Science and Technology University of Cambridge United Kingdom Interdepartmental Graduate Program in Dynamical Neuroscience University of California Santa Barbara United States
Recently, Koopman operator theory has become a powerful tool for developing linear representations of non-linear dynamical systems. However, existing data-driven applications of Koopman operator theory, including both... 详细信息
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Optimizing neural networks via koopman operator theory  20
Optimizing neural networks via koopman operator theory
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Proceedings of the 34th International Conference on Neural Information Processing Systems
作者: Akshunna S. Dogra William T. Redman John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA Interdeparmental Graduate Program in Dynamical Neuroscience University of California Santa Barbara Santa Barbara CA
Koopman operator theory, a powerful framework for discovering the underlying dynamics of nonlinear dynamical systems, was recently shown to be intimately connected with neural network training. In this work, we take t...
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Control of ecological outcomes through deliberate parameter changes in a model of the gut microbiome
arXiv
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arXiv 2019年
作者: Wang, Zipeng Jones, Eric W. Mueller, Joshua M. Carlson, Jean M. Department of Physics University of California Santa Barbara Santa BarbaraCA United States Interdepartmental Graduate Program in Dynamical Neuroscience University of California Santa Barbara Santa BarbaraCA United States
The generalized Lotka-Volterra (gLV) equations are a mathematical proxy for ecological dynamics. We focus on a gLV model of the gut microbiome, in which the evolution of the gut microbial state is determined in part b... 详细信息
来源: 评论
Local error quantification for efficient neural network dynamical system solvers
arXiv
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arXiv 2020年
作者: Dogra, Akshunna S. Redman, William T. John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Interdepartmental Graduate Program in Dynamical Neuroscience University of California Santa BarbaraCA93106 United States
Neural Networks have been identified as potentially powerful tools for the study of complex systems. A noteworthy example is the Neural Network Differential Equation (NN DE) solver, which can provide functional approx... 详细信息
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