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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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training data Building transformer-like AI models which can predict DNA structures Performing experiments for validation Participation in conferences in Germany and abroad (including presenting your research
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
Searches related to machine learning prediction modelling
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