委托
发表于 2025-3-26 21:06:06
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钢笔尖
发表于 2025-3-27 03:21:56
Serial Order Codes for Dimensionality Reduction in the Learning of Higher-Order Rules and Compositiok for neural networks. One of the mechanisms that allows to capture hierarchical dependencies between items within sequences is ordinal coding. Ordinal patterns create a grammar, or a set of rules, that reduces the dimensionality of the search space and that can be used in a generative manner to com
indignant
发表于 2025-3-27 05:34:58
Sparsity Aware Learning in Feedback-Driven Differential Recurrent Neural Networks effective learning of variable information gain makes training d-RNNs important for their inherent derivative of states property. In addition to training readout weights, the optimization of the intrinsic recurrent connection of the d-RNNs prove significant for performance enhancement. We introduce
Spina-Bifida
发表于 2025-3-27 13:00:12
Towards Scalable GPU-Accelerated SNN Training via Temporal Fusionosely emulating the complex dynamics of biological neural networks. While SNNs show promising efficiency on specialized sparse-computational hardware, their practical training often relies on conventional GPUs. This reliance frequently leads to extended computation times when contrasted with traditi
绝种
发表于 2025-3-27 14:44:32
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真实的人
发表于 2025-3-27 19:00:48
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adj忧郁的
发表于 2025-3-27 23:09:33
Dynamic Graph for Biological Memory Modeling: A System-Level Validation, but traditional graph models are static, lack the dynamic and autonomous behaviors of biological neural networks, rely on algorithms with a global view. This study introduces a novel dynamic directed graph model that simulates the brain’s memory process by empowering each node with adaptive learni
Bravado
发表于 2025-3-28 02:17:29
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搜寻
发表于 2025-3-28 06:59:36
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REIGN
发表于 2025-3-28 13:17:58
Revealing Functions of Extra-Large Excitatory Postsynaptic Potentials: Insights from Dynamical Chara-tailed excitatory postsynaptic potentials (EPSPs), involving a minority of extra-large (XL) EPSPs, are currently garnering much attention, which strongly relates to cognitive functions. In addition to physiological studies, mathematical modeling approaches are effective in neuroscience because they