Computational simulations indicate that classical psychedelics could induce hallucinations by co-opting neural circuitry dedicated to sleep-dependent replay and consolidation, providing a theoretical ...
Abstract: Neural networks have become increasingly popular in recent years due to their ability to efficiently solve a wide range of complex problems, including computer vision, machine translation, ...
Biologically plausible learning mechanisms have implications for understanding brain functions and engineering intelligent systems. Inspired by the multi-scale recurrent connectivity in the brain, we ...
ABSTRACT: Machine learning (ML) has become an increasingly central component of high-energy physics (HEP), providing computational frameworks to address the growing complexity of theoretical ...
Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks
Abstract: Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in ...
ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...
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