心痛 发表于 2025-3-25 05:55:11

Cornelius Bickel,Sebastian Klaukeral output signals are encoded as a sum of shifted power-law kernels. Simple greedy thresholding can compute this encoding, and spike-trains are then exactly the signal’s fractional derivative. Fractionally predictive spike-coding exploits natural statistics and is consistent with observed spike-rat

Oratory 发表于 2025-3-25 08:13:18

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Tincture 发表于 2025-3-25 12:38:47

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柏树 发表于 2025-3-25 17:04:46

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debouch 发表于 2025-3-25 20:26:33

https://doi.org/10.1007/978-3-322-85606-7er to interact in this complex and changing environment, according to the active perception theory, the agent needs to learn the correlations between its actions and the changes they induce in the environment. In the perspective of a bio-inspired architecture for the learning of multi-modal correlat

富足女人 发表于 2025-3-26 00:09:01

https://doi.org/10.1007/978-3-322-85606-7with the forward projection. However, the wide terminal arbors of individual axons limit the precision of such anatomical reciprocity. This leaves open the question of whether more precise reciprocal connectivity is obtainable through the adjustment of synaptic strengths. We have found that such a s

放逐 发表于 2025-3-26 06:05:23

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hypertension 发表于 2025-3-26 09:16:20

https://doi.org/10.1007/978-3-662-33998-5ple classifiers were introduced. An interesting kind of methods creates a hierarchy of sub-problems by clustering prototypes of each one of the classes, but the solution produced by the clustering stage is heavily influenced by the label’s information. In this work we introduce a new strategy to sol

问到了烧瓶 发表于 2025-3-26 13:11:55

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Extort 发表于 2025-3-26 19:41:58

Fermat’s Last Theorem for Amateursatching substructures are considered independently from their position within the trees. However, when a match happens in similar positions, more strength could reasonably be given to it. Here, we give a systematic way to enrich a large class of tree kernels with this kind of information without aff
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查看完整版本: Titlebook: Artificial Neural Networks and Machine Learning- ICANN 2011; 21st International C Timo Honkela,Włodzisław Duch,Samuel Kaski Conference proc