Abstract: Convolutional neural networks (CNNs) have wide applications in pattern recognition and image processing. Despite recent advances, much remains to be done for CNNs to learn a better ...

In order to understand the functionality of neural networks, reliable parallel spike trains must be recorded from neuronal ensembles [1, 2]. Silicon-based multi-transistor arrays ('Neurochips') are ...

Abstract: As a fundamental mathematical problem in the field of machine learning, the linear separability test still lacks a theoretically complete and computationally efficient method. This paper ...

Entanglement or non-separability constitutes a cornerstone of quantum mechanics from which many of its unique characteristics arise. For example, non-separability in entangled particle pairs leads to ...

This paper investigates the role of informality in affecting the magnitude of the fiscal multiplier in a panel of 141 countries, using the local projections method. We find a strong negative ...

This post is in response to Can Quantum Physics Hold the Key to Happiness? By Chris Gilbert, M.D., Ph.D. Hopefully, we have all experienced lots of love. What is love? I've come to the conclusion that ...

This paper provides general and empirically implementable sufficient statistics formulas for optimal nonlinear tax systems in the presence of across-income heterogeneity in preferences, inheritances, ...

This post is in response to Quantum Effects In the Brain By Robert Lanza M.D. In his 2019 New York Times opinion piece entitled, “Even Physicists Don’t Understand Quantum Mechanics. Worse, they don’t ...