Niclas Ståhl

University of Skövde — Sweden

Computer Science · Physical Sciences

8h-index439citations20works0.02yr avg
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Research Topics

Computational Drug Discovery Methods(6), Fault Detection and Control Systems(4), Receptor Mechanisms and Signaling(4), Innovative Microfluidic and Catalytic Techniques Innovation(3), Anomaly Detection Techniques and Applications(3)

Publications20 total

Identifying wetland areas in historical maps using deep convolutional neural networks
Ecological Informatics·2022· 24 citedOpen Access
Utilising Data from Multiple Production Lines for Predictive Deep Learning Models
Lecture notes in networks and systems·2021
Identifying Wetland Areas in Historical Maps using Deep Convolutional Neural Networks
arXiv (Cornell University)·2021Open Access
Using Reinforcement Learning for Generating Polynomial Models to Explain Complex Data
SN Computer Science·2021· 2 citedOpen Access
Understanding Robust Target Prediction in Basic Oxygen Furnace
2021
Using Machine Learning for Robust Target Prediction in a Basic Oxygen Furnace System
Metallurgical and Materials Transactions B·2020· 47 citedOpen Access
Evaluation of Uncertainty Quantification in Deep Learning
Communications in computer and information science·2020· 40 citedOpen Access
Deep Reinforcement Learning for Multiparameter Optimization in <i>de novo</i> Drug Design
Journal of Chemical Information and Modeling·2019· 204 cited
Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design
2019· 4 citedOpen Access
Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design
2019· 45 citedOpen Access
Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design
2019· 1 citedOpen Access
Using recurrent neural networks with attention for detecting problematic slab shapes in steel rolling
Applied Mathematical Modelling·2019· 37 cited
Deep Convolutional Neural Networks for the Prediction of Molecular Properties: Challenges and Opportunities Connected to the Data
Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics·2018· 19 citedOpen Access
Machine Learning: A Concise Overview
Studies in big data·2018· 15 cited
Complex Data Analysis
Studies in big data·2018
Improving the Use of Deep Convolutional Neural Networks for the Prediction of Molecular Properties
Advances in intelligent systems and computing·2018
A Self-Organizing Ensemble of Deep Neural Networks for the Classification of Data from Complex Processes
Communications in computer and information science·2018· 1 cited
Challenges and opportunities of analysing complex data using deep learning
KTH Publication Database DiVA (KTH Royal Institute of Technology)·2017Open Access
The Effect of Sexual Selection on Cline Patterns in Biological Traits
Chalmers Publication Library (Chalmers University of Technology)·2016Open Access
Formalisering av algoritmer och matematiska bevis En formalisering av Toom-Cook algoritmen i Coq med SSReflect
Gothenburg University Publications Electronic Archive (Gothenburg University)·2014Open Access

Frequent Co-authors

Gunnar Mathiason(13), Alexander Karlsson(10), Göran Falkman(9), Jonas Boström(6), Juhee Bae(4), Yurong Li(2), Niklas Kojola(2), Lisa Weimann(2), Denio Duarte(1), Dellainey Alcaçoas(1), Jesper Andersson(1), Åsa Lideström(1), Daniel Oom(1), Anders Sjöberg(1), Jonas Mellin(1), Vicenç Torra(1)