Status:
+44 1865 270509
Research groups:
Address
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Woodstock Road
Oxford
OX2 6GG
Recent Publications:
Numerically solving parametric families of high-dimensional Kolmogorov partial differential equations via deep learning
Advances in Neural Information Processing Systems 33 (NeurIPS 2020)
page 1-13
(10 December 2020)
Research interests:
- Machine learning and deep learning
- Graphs and Networks
- Chemoinformatics and computational drug-discovery
Prizes, awards, and scholarships:
2016/2017: Most Outstanding MRes Research Student at the UCL Center of Mathematics and Physics in the Life Sciences and Experimental Biology (UCL CoMPLEX)
Major / recent publications:
Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning
J. Berner, M. Dablander, P. Grohs
In: Advances in Neural Information Processing Systems 33 (NeurIPS 2020). arXiv
Multivariate Network Analysis of Cerebral and Systemic Variables for Assessement of Injury Following Hypoxic Ischaemic Encephalopathy
M. Dablander, S. Mitra, G. Bale, M. Dinan, C. Uria-Avellanal, D. Price, M. Sokolska, A. Bainbridge, G. Kendall, J. Meek, I. Tachtsidis, N. Robertson
In: Summer Meeting of The Neonatal Society (Brighton, UK, 2017)
Direct and Iterative Implementations of the Spectral Chebyshev Method for the 2D Poisson Equation
M. Dablander, I. Vrubleuski, V. Volkov
In: International Scientific and Practical Conference (Brest, Belarus, 2015)