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Program
Date | Speaker | Affiliation | Topic | |
---|---|---|---|---|
2021.01.27 | Arif Sinan Uslu | University of Luxembourg | The effect of self-paced neurofeedback on EEG learning: An experimental setup | details |
2021.01.20 | Milad Zeraatpisheh | University of Luxembourg | Bayesian neural networks and MC Dropout; ways to measure uncertainty in Deep learning | details |
2021.01.13 | Lars Beex | University of Luxembourg | Unsupervised learning to select modes for reduced-order models of hyperelastoplasticity: application to RVEs | details |
2020.12.16 | Erkan Oterkus | University of Strathclyde | A Physics-guided Machine Learning Model Based on Peridynamics | details |
2020.12.09 | Eleni Koronaki | University of Luxembourg | From partial data to out-of-sample parameter and observation estimation with Diffusion Maps and Geometric Harmonics | details |
2020.12.02 | Vivek OOmmen | Indian Institute of Technology Madras | The effectiveness of PINNs in solving inverse heat transfer problems | details |
2020.11.25 | Anina Šarkić | University of Luxembourg | Machine Learning in Wind Engineering | details |
2020.11.18 | Diego Kozlowski | University of Luxembourg | Machine Learning on graphs | details |
2020.11.11 | Tittu Mathew | Indian Institute of Technology Madras | Bayesian uncertainty quantification and model selection | details |
2020.11.04 | Arnaud Mazier | University of Luxembourg | Decision Trees methods, an overview of the white-boxes | details |
2020.10.28 | Cosmin Anitescu | Bauhaus-Universität Weimar | Methods Based on Artificial Neural Networks for the Solution of Partial Differential Equations | details |
2020.10.21 | Eleni Koronaki | University of Luxembourg | “Dinky, Dirty, Dynamic & Deceptive Data (1)”: An overview of hybrid machine learning and equation-based modelling | details |
2020.10.14 | Saurabh Deshpande | University of Luxembourg | Data Driven Hyper-elastic Simulations | details |
2020.10.07 | Vasilis Krokos | University of Cardiff & Synopsys-Simpleware | Bayesian Neural Networks for uncertainty estimation on regression problems | details |