Zobrazeno 1 - 10
of 131
pro vyhledávání: '"Ravichandran, Naresh"'
Neural networks that can capture key principles underlying brain computation offer exciting new opportunities for developing artificial intelligence and brain-like computing algorithms. Such networks remain biologically plausible while leveraging loc
Externí odkaz:
http://arxiv.org/abs/2406.04733
Networks of interconnected neurons communicating through spiking signals offer the bedrock of neural computations. Our brains spiking neural networks have the computational capacity to achieve complex pattern recognition and cognitive functions effor
Externí odkaz:
http://arxiv.org/abs/2406.03054
Associative memory or content addressable memory is an important component function in computer science and information processing and is a key concept in cognitive and computational brain science. Many different neural network architectures and lear
Externí odkaz:
http://arxiv.org/abs/2401.00335
We introduce a novel spiking neural network model for learning distributed internal representations from data in an unsupervised procedure. We achieved this by transforming the non-spiking feedforward Bayesian Confidence Propagation Neural Network (B
Externí odkaz:
http://arxiv.org/abs/2305.03866
Associative memory has been a prominent candidate for the computation performed by the massively recurrent neocortical networks. Attractor networks implementing associative memory have offered mechanistic explanation for many cognitive phenomena. How
Externí odkaz:
http://arxiv.org/abs/2206.15036
Autor:
Ravichandran, Naresh Kumar, Kim, HyeMi, Park, Joonha, Hur, Hwan, Kim, Jinsung, Bae, Ji Yong, Hyun, Sangwon, Kim, I Jong, Kim, Dong Uk, Lee, Sang-Chul, Chang, Ki Soo, Muniraj, Inbarasan, Jeon, Jessie S., Nam, Ki-Hwan, Lee, Kye-Sung
Publikováno v:
In Optics and Laser Technology December 2024 179
Autor:
Luna, Jannat Amrin, Wijesinghe, Ruchire Eranga, Lee, Seung-Yeol, Ravichandran, Naresh Kumar, Saleah, Sm Abu, Seong, Daewoon, Jung, Hee-Young, Jeon, Mansik, Kim, Jeehyun
Publikováno v:
In Optik April 2024 301
Learning internal representations from data using no or few labels is useful for machine learning research, as it allows using massive amounts of unlabeled data. In this work, we use the Bayesian Confidence Propagation Neural Network (BCPNN) model de
Externí odkaz:
http://arxiv.org/abs/2106.15546
Autor:
Podobas, Artur, Svedin, Martin, Chien, Steven W. D., Peng, Ivy B., Ravichandran, Naresh Balaji, Herman, Pawel, Lansner, Anders, Markidis, Stefano
The modern deep learning method based on backpropagation has surged in popularity and has been used in multiple domains and application areas. At the same time, there are other -- less-known -- machine learning algorithms with a mature and solid theo
Externí odkaz:
http://arxiv.org/abs/2106.05373
Autor:
Luna, Jannat Amrin, Ravichandran, Naresh Kumar, Saleah, Sm Abu, Wijesinghe, Ruchire Eranga, Seong, Daewoon, Choi, Kwang Shik, Jung, Hee-Young, Jeon, Mansik, Kim, Jeehyun
Publikováno v:
In Optics and Laser Technology January 2024 168