Paul Scherer - RankMe

13 papers A 1Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	When three experiments are better than two: Avoiding intractable correlated aleatoric uncertainty by leveraging a novel bias-variance tradeoff. CoRR Paul Scherer, Andreas Kirsch, Jake P. Taylor-King
2022	J	`jnl`	Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery. CoRR Yana Lishkova, Paul Scherer, Steffen Ridderbusch, Mateja Jamnik, Pietro Liò, Sina Ober-Blöbaum, Christian Offen
2022	—	`conf`	Distributed Representations of Graphs for Drug Pair Scoring. LoG Paul Scherer, Pietro Liò, Mateja Jamnik
2022	J	`jnl`	Distributed representations of graphs for drug pair scoring. CoRR Paul Scherer, Pietro Liò, Mateja Jamnik
2022	J	`jnl`	PyRelationAL: A Library for Active Learning Research and Development. CoRR Paul Scherer, Thomas Gaudelet, Alison Pouplin, Suraj M. S, Jyothish Soman, Lindsay Edwards, Jake P. Taylor-King
2022	J	`jnl`	Unsupervised construction of computational graphs for gene expression data with explicit structural inductive biases. Bioinform. Paul Scherer, Maja Trebacz, Nikola Simidjievski, Ramón Viñas, Zohreh Shams, Helena Andrés-Terré, Mateja Jamnik, Pietro Liò
2021	J	`jnl`	Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks. CoRR Benedek Rozemberczki, Paul Scherer, Oliver Kiss, Rik Sarkar, Tamas Ferenci
2021	A	`conf`	PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models. CIKM Benedek Rozemberczki, Paul Scherer, Yixuan He, George Panagopoulos, Alexander Riedel, Maria Sinziana Astefanoaei, Oliver Kiss, Ferenc Béres, Guzmán López, Nicolas Collignon, Rik Sarkar
2021	J	`jnl`	PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models. CoRR Benedek Rozemberczki, Paul Scherer, Yixuan He, George Panagopoulos, Maria Sinziana Astefanoaei, Oliver Kiss, Ferenc Béres, Nicolas Collignon, Rik Sarkar
2020	J	`jnl`	Incorporating network based protein complex discovery into automated model construction. CoRR Paul Scherer, Maja Trebacz, Nikola Simidjievski, Zohreh Shams, Helena Andrés-Terré, Pietro Liò, Mateja Jamnik
2020	J	`jnl`	Learning distributed representations of graphs with Geo2DR. CoRR Paul Scherer, Pietro Liò
2020	J	`jnl`	Using ontology embeddings for structural inductive bias in gene expression data analysis. CoRR Maja Trebacz, Zohreh Shams, Mateja Jamnik, Paul Scherer, Nikola Simidjievski, Helena Andrés-Terré, Pietro Liò
2019	J	`jnl`	Decoupling feature propagation from the design of graph auto-encoders. CoRR Paul Scherer, Helena Andrés-Terré, Pietro Liò, Mateja Jamnik