research
∙
12/17/2020
On the performance of deep learning for numerical optimization: an application to protein structure prediction
Deep neural networks have recently drawn considerable attention to build...
share
research
∙
04/12/2020
Bypassing or flying above the obstacles? A novel multi-objective UAV path planning problem
This study proposes a novel multi-objective integer programming model fo...
research
∙
09/20/2019
From feature selection to continuous optimization
Metaheuristic algorithms (MAs) have seen unprecedented growth thanks to ...
research
∙
09/20/2019
From feature selection to continues optimization
Metaheuristic algorithms (MAs) have seen unprecedented growth thanks to ...
research
∙
09/11/2019
InceptionTime: Finding AlexNet for Time Series Classification
Time series classification (TSC) is the area of machine learning interes...
research
∙
09/11/2019
DreamTime: Finding AlexNet for Time Series Classification
Time series classification (TSC) is the area of machine learning interes...
research
∙
08/20/2019
Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks
Purpose: Manual feedback from senior surgeons observing less experienced...
research
∙
12/02/2018
Automatic hyperparameter selection in Autodock
Autodock is a widely used molecular modeling tool which predicts how sma...
research
∙
11/05/2018
Transfer learning for time series classification
Transfer learning for deep neural networks is the process of first train...
research
∙
09/12/2018
Deep learning for time series classification: a review
Time Series Classification (TSC) is an important and challenging problem...
research
∙
08/07/2018
Data augmentation using synthetic data for time series classification with deep residual networks
Data augmentation in deep neural networks is the process of generating a...
research
∙
06/07/2018
