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Entropy

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A heuristic perspective on non-variational free energy modulation at the sleep-like edge.

Bio Systems
BACKGROUND: The variational Free Energy Principle (FEP) establishes that a neural system minimizes a free energy function of their internal state through environmental sensing entailing beliefs about hidden states in their environment.

Self-paced and self-consistent co-training for semi-supervised image segmentation.

Medical image analysis
Deep co-training has recently been proposed as an effective approach for image segmentation when annotated data is scarce. In this paper, we improve existing approaches for semi-supervised segmentation with a self-paced and self-consistent co-trainin...

Eigenvalue-based entropy in directed complex networks.

PloS one
Entropy is an important index for describing the structure, function, and evolution of network. The existing research on entropy is primarily applied to undirected networks. Compared with an undirected network, a directed network involves a special a...

An integrated fuzzy sustainable supplier evaluation and selection framework for green supply chains in reverse logistics.

Environmental science and pollution research international
Green supply chain management considers the environmental effects of all activities related to the supply chain, from obtaining raw materials to the final delivery of finished goods. Selecting the right supplier is a critical decision in green supply...

The influence of random number generation in dissipative particle dynamics simulations using a cryptographic hash function.

PloS one
The tiny encryption algorithm (TEA) is widely used when performing dissipative particle dynamics (DPD) calculations in parallel, usually on distributed memory systems. In this research, we reduced the computational cost of the TEA hash function and i...

Impulsive Synchronization of Unbounded Delayed Inertial Neural Networks With Actuator Saturation and Sampled-Data Control and its Application to Image Encryption.

IEEE transactions on neural networks and learning systems
The article considers the impulsive synchronization for inertial neural networks with unbounded delay and actuator saturation via sampled-data control. Based on an impulsive differential inequality, the difficulties caused by unbounded delay and impu...

Life as a self-referential deep learning system: A quantum-like Boltzmann machine model.

Bio Systems
It has been empirically found that the income structure of market-economy societies obeys a Boltzmann-like income distribution. The empirical evidence has covered more than 66 countries. In this paper, we show that when a human society obeys a Boltzm...

Fast convergence rates of deep neural networks for classification.

Neural networks : the official journal of the International Neural Network Society
We derive the fast convergence rates of a deep neural network (DNN) classifier with the rectified linear unit (ReLU) activation function learned using the hinge loss. We consider three cases for a true model: (1) a smooth decision boundary, (2) smoot...

Learning Atomic Interactions through Solvation Free Energy Prediction Using Graph Neural Networks.

Journal of chemical information and modeling
Solvation free energy is a fundamental property that influences various chemical and biological processes, such as reaction rates, protein folding, drug binding, and bioavailability of drugs. In this work, we present a deep learning method based on g...

New machine learning and physics-based scoring functions for drug discovery.

Scientific reports
Scoring functions are essential for modern in silico drug discovery. However, the accurate prediction of binding affinity by scoring functions remains a challenging task. The performance of scoring functions is very heterogeneous across different tar...