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Niclas Ståhl
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2020 – today
- 2022
- [j4]Niclas Ståhl, Lisa Weimann:
Identifying wetland areas in historical maps using deep convolutional neural networks. Ecol. Informatics 68: 101557 (2022) - [c5]Ulf Johansson, Tuwe Löfström, Niclas Ståhl:
Well-Calibrated Rule Extractors. COPA 2022: 72-91 - 2021
- [b1]Niclas Ståhl:
Integrating domain knowledge into deep learning: Increasing model performance through human expertise. University of Skövde, Sweden, 2021 - [j3]Niclas Ståhl, Gunnar Mathiason, Dellainey Alcacoas:
Using Reinforcement Learning for Generating Polynomial Models to Explain Complex Data. SN Comput. Sci. 2(2): 103 (2021) - [c4]Niclas Ståhl, Gunnar Mathiason, Juhee Bae:
Utilising Data from Multiple Production Lines for Predictive Deep Learning Models. DCAI (1) 2021: 67-76 - [i1]Niclas Ståhl, Lisa Weimann:
Identifying Wetland Areas in Historical Maps using Deep Convolutional Neural Networks. CoRR abs/2108.04107 (2021) - 2020
- [c3]Niclas Ståhl, Göran Falkman, Alexander Karlsson, Gunnar Mathiason:
Evaluation of Uncertainty Quantification in Deep Learning. IPMU (1) 2020: 556-568
2010 – 2019
- 2019
- [j2]Niclas Ståhl, Göran Falkman, Alexander Karlsson, Gunnar Mathiason, Jonas Boström:
Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design. J. Chem. Inf. Model. 59(7): 3166-3176 (2019) - [j1]Niclas Ståhl, Göran Falkman, Alexander Karlsson, Gunnar Mathiason, Jonas Boström:
Deep Convolutional Neural Networks for the Prediction of Molecular Properties: Challenges and Opportunities Connected to the Data. J. Integr. Bioinform. 16(1) (2019) - [p2]Denio Duarte, Niclas Ståhl:
Machine Learning: A Concise Overview. Data Science in Practice 2019: 27-58 - [p1]Juhee Bae, Alexander Karlsson, Jonas Mellin, Niclas Ståhl, Vicenç Torra:
Complex Data Analysis. Data Science in Practice 2019: 157-169 - 2018
- [c2]Niclas Ståhl, Göran Falkman, Gunnar Mathiason, Alexander Karlsson:
A Self-Organizing Ensemble of Deep Neural Networks for the Classification of Data from Complex Processes. IPMU (3) 2018: 248-259 - [c1]Niclas Ståhl, Göran Falkman, Alexander Karlsson, Gunnar Mathiason, Jonas Boström:
Improving the Use of Deep Convolutional Neural Networks for the Prediction of Molecular Properties. PACBB 2018: 71-79
Coauthor Index
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