Markus Dablander

MRes, MSc, BSc

Status

Postgraduate Student

Research groups

Address
Mathematical Institute
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

Berner, J Dablander, M Grohs, P Advances in Neural Information Processing Systems 33 (NeurIPS 2020) 1-13 (10 Dec 2020)

Research interests

Machine learning and deep learning
Graphs and Networks
Chemoinformatics and computational drug-discovery

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)

Teaching

C6.5 Theories of Deep Learning: Teaching Assistant, MT 2021

C5.4 Networks: Teaching Assistant, HT 2021

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)