AIMC Topic:
Computer Simulation

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Multistability and associative memory of neural networks with Morita-like activation functions.

Neural networks : the official journal of the International Neural Network Society
This paper presents the multistability analysis and associative memory of neural networks (NNs) with Morita-like activation functions. In order to seek larger memory capacity, this paper proposes Morita-like activation functions. In a weakened condit...

Towards a mathematical framework to inform neural network modelling via polynomial regression.

Neural networks : the official journal of the International Neural Network Society
Even when neural networks are widely used in a large number of applications, they are still considered as black boxes and present some difficulties for dimensioning or evaluating their prediction error. This has led to an increasing interest in the o...

How Blue is the Sky?

eNeuro
The recent trend toward an industrialization of brain exploration and the technological prowess of artificial intelligence algorithms and high-performance computing has caught the imagination of the public. These impressive advances are fueling an un...

Promotion time cure rate model with a neural network estimated nonparametric component.

Statistics in medicine
Promotion time cure rate models (PCM) are often used to model the survival data with a cure fraction. Medical images or biomarkers derived from medical images can be the key predictors in survival models. However, incorporating images in the PCM is c...

Advances in Predictions of Oral Bioavailability of Candidate Drugs in Man with New Machine Learning Methodology.

Molecules (Basel, Switzerland)
Oral bioavailability (F) is an essential determinant for the systemic exposure and dosing regimens of drug candidates. F is determined by numerous processes, and computational predictions of human estimates have so far shown limited results. We descr...

Automatic control of simulated moving bed process with deep Q-network.

Journal of chromatography. A
Optimal control of a simulated moving bed (SMB) process is challenging because the system dynamics is represented as nonlinear partial differential-algebraic equations combined with discrete events. In addition, product purity constraints are active ...

WormPose: Image synthesis and convolutional networks for pose estimation in C. elegans.

PLoS computational biology
An important model system for understanding genes, neurons and behavior, the nematode worm C. elegans naturally moves through a variety of complex postures, for which estimation from video data is challenging. We introduce an open-source Python packa...

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...

Improving axial resolution in Structured Illumination Microscopy using deep learning.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Structured Illumination Microscopy (SIM) is a widespread methodology to image live and fixed biological structures smaller than the diffraction limits of conventional optical microscopy. Using recent advances in image up-scaling through deep learning...

Predicting Absorption-Distribution Properties of Neuroprotective Phosphine-Borane Compounds Using In Silico Modeling and Machine Learning.

Molecules (Basel, Switzerland)
Phosphine-borane complexes are novel chemical entities with preclinical efficacy in neuronal and ophthalmic disease models. In vitro and in vivo studies showed that the metabolites of these compounds are capable of cleaving disulfide bonds implicated...