AIMC Topic: Algorithms

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Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction.

Journal of computer-aided molecular design
Machine learning methods may have the potential to significantly accelerate drug discovery. However, the increasing rate of new methodological approaches being published in the literature raises the fundamental question of how models should be benchm...

An Optimal Electrical Impedance Tomography Drive Pattern for Human-Computer Interaction Applications.

IEEE transactions on biomedical circuits and systems
In this article, we presented an optimal Electrical Impedance Tomography (EIT) drive pattern based on feature selection and model explanation, and proposed a portable EIT system for applications in human-computer interaction for gesture recognition a...

Diagnosis and classification of cancer using hybrid model based on ReliefF and convolutional neural network.

Medical hypotheses
Machine learning and deep learning methods aims to discover patterns out of datasets such as, microarray data and medical data. In recent years, the importance of producing microarray data from tissue and cell samples and analyzing these microarray d...

Machine learning approaches for analyzing and enhancing molecular dynamics simulations.

Current opinion in structural biology
Molecular dynamics (MD) has become a powerful tool for studying biophysical systems, due to increasing computational power and availability of software. Although MD has made many contributions to better understanding these complex biophysical systems...

Application of artificial neural networks to describe the combined effect of pH, time, NaCl and ethanol concentrations on the biofilm formation of Staphylococcus aureus.

Microbial pathogenesis
Biofilms are organized communities, adherent to the surface and resistant to adverse environmental and antimicrobial agents. So, its control is very important. Staphylococcus aureus is an opportunistic pathogen with the biofilm-forming ability that c...

Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Although double-precision floating-point arithmetic currently dominates high-performance computing, there is increasing interest in smaller and simpler arithmetic types. The main reasons are potential improvements in energy efficiency and memory foot...

Rethinking arithmetic for deep neural networks.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
We consider efficiency in the implementation of deep neural networks. Hardware accelerators are gaining interest as machine learning becomes one of the drivers of high-performance computing. In these accelerators, the directed graph describing a neur...

Optimal memory-aware backpropagation of deep join networks.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Deep learning training memory needs can prevent the user from considering large models and large batch sizes. In this work, we propose to use techniques from memory-aware scheduling and automatic differentiation (AD) to execute a backpropagation grap...

Crowd of Oz: A Crowd-Powered Social Robotics System for Stress Management.

Sensors (Basel, Switzerland)
Coping with stress is crucial for a healthy lifestyle. In the past, a great deal of research has been conducted to use socially assistive robots as a therapy to alleviate stress and anxiety related problems. However, building a fully autonomous socia...

A Machine Learning Approach to Growth Direction Finding for Automated Planting of Bulbous Plants.

Scientific reports
In agricultural robotics, a unique challenge exists in the automated planting of bulbous plants: the estimation of the bulb's growth direction. To date, no existing work addresses this challenge. Therefore, we propose the first robotic vision framewo...