Paul Scherer
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Variational autoencoders for cancer data integration: design principles and computational practice
N Simidjievski, C Bodnar, I Tariq, P Scherer, HA Terre, Z Shams, ...
Frontiers in Genetics 10, 2019
Associations between maternal physical activity in early and late pregnancy and offspring birth size: remote federated individual level meta‐analysis from eight cohort studies
S Pastorino, T Bishop, SR Crozier, C Granström, K Kordas, LK Küpers, ...
BJOG: An International Journal of Obstetrics & Gynaecology 126 (4), 459-470, 2019
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models
B Rozemberczki, P Scherer, Y He, G Panagopoulos, M Astefanoaei, ...
arXiv preprint arXiv:2104.07788, 2021
REM: An Integrative Rule Extraction Methodology for Explainable Data Analysis in Healthcare
Z Shams, B Dimanov, S Kola, N Simidjievski, HA Terre, P Scherer, ...
bioRxiv, 2021
Using ontology embeddings for structural inductive bias in gene expression data analysis
M Trębacz, Z Shams, M Jamnik, P Scherer, N Simidjievski, HA Terre, ...
15th Machine Learning in Computational Biology (MLCB'20), 2020
Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks
B Rozemberczki, P Scherer, O Kiss, R Sarkar, T Ferenci
WWW’21: Graph Learning Benchmarks Workshop, 2021
Learning distributed representations of graphs with Geo2DR
P Scherer, P Lio
Graph Representation Learning and Beyond Workshop (ICML'20), 2020
Incorporating network based protein complex discovery into automated model construction
P Scherer, M Trȩbacz, N Simidjievski, Z Shams, H Andres Terre, P Liň, ...
15th Machine Learning in Computational Biology (MLCB'20), 2020
Decoupling feature propagation from the design of graph auto-encoders
P Scherer, H Andres-Terre, P Lio, M Jamnik
arXiv preprint arXiv:1910.08589, 2019
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