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» Refractoriness and Neural Precision
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IWANN
2005
Springer
15 years 5 months ago
Co-evolutionary Learning in Liquid Architectures
A large class of problems requires real-time processing of complex temporal inputs in real-time. These are difficult tasks for state-of-the-art techniques, since they require captu...
Igal Raichelgauz, Karina Odinaev, Yehoshua Y. Zeev...
FPL
2009
Springer
161views Hardware» more  FPL 2009»
15 years 4 months ago
A multi-FPGA architecture for stochastic Restricted Boltzmann Machines
Although there are many neural network FPGA architectures, there is no framework for designing large, high-performance neural networks suitable for the real world. In this paper, ...
Daniel L. Ly, Paul Chow
BMCBI
2005
122views more  BMCBI 2005»
14 years 12 months ago
A neural strategy for the inference of SH3 domain-peptide interaction specificity
Background: The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that gen...
Enrico Ferraro, Allegra Via, Gabriele Ausiello, Ma...
NIPS
2007
15 years 1 months ago
An in-silico Neural Model of Dynamic Routing through Neuronal Coherence
We describe a neurobiologically plausible model to implement dynamic routing using the concept of neuronal communication through neuronal coherence. The model has a three-tier arc...
Devarajan Sridharan, Brian Percival, John V. Arthu...
BMCBI
2007
207views more  BMCBI 2007»
15 years 3 days ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...