Michael Scholkemper

15 papers A* 3Misc 2Journal 9Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Causal Cellular Context Transfer Learning (C3TL): An Efficient Architecture for Prediction of Unseen Perturbation Effects.
CoRR
Michael Scholkemper, Sach Mukherjee
2025 A* conf
Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs.
ICLR
Michael Scholkemper, Xinyi Wu, Ali Jadbabaie, Michael T. Schaub
2024 Misc conf
A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings.
ICASSP
Michael Scholkemper, Damin Kühn, Gerion Nabbefeld, Simon Musall, Björn Kampa, Michael T. Schaub
2024 J jnl
A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings.
CoRR
Michael Scholkemper, Damin Kühn, Gerion Nabbefeld, Simon Musall, Björn Kampa, Michael T. Schaub
2024 J jnl
Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs.
CoRR
Michael Scholkemper, Xinyi Wu, Ali Jadbabaie, Michael T. Schaub
2023 A* conf
An Optimization-based Approach To Node Role Discovery in Networks: Approximating Equitable Partitions.
NeurIPS
Michael Scholkemper, Michael T. Schaub
2023 J jnl
An Optimization-based Approach To Node Role Discovery in Networks: Approximating Equitable Partitions.
CoRR
Michael Scholkemper, Michael T. Schaub
2023 J jnl
ICML 2023 Topological Deep Learning Challenge : Design and Results.
CoRR
Mathilde Papillon, Mustafa Hajij, Florian Frantzen, Josef Hoppe, Helen Jenne, Johan Mathe, Audun Myers, Theodore Papamarkou, Michael T. Schaub, Ghada Zamzmi, Tolga Birdal, Tamal K. Dey, Tim Doster, Tegan Emerson, Gurusankar Gopalakrishnan, Devendra Govil, Vincent P. Grande, Aldo Guzmán-Sáenz, Henry Kvinge, Neal Livesay, Jan Meissner, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Maneel Reddy Karri, Paul Rosen, Sophia Sanborn, Michael Scholkemper, Robin Walters, Jens Agerberg, Georg Bökman, Sadrodin Barikbin, Claudio Battiloro, Gleb Bazhenov, Guillermo Bernárdez, Aiden Brent, Sergio Escalera, Simone Fiorellino, Dmitrii Gavrilev, Mohammed Hassanin, Paul Häusner, Odin Hoff Gardaa, Abdelwahed Khamis, Manuel Lecha, German Magai, Tatiana Malygina, Pavlo Melnyk, et al.
2023 — conf
ICML 2023 Topological Deep Learning Challenge: Design and Results.
TAG-ML
Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane
2023 J jnl
Learning the effective order of a hypergraph dynamical system.
CoRR
Leonie Neuhäuser, Michael Scholkemper, Francesco Tudisco, Michael T. Schaub
2023 A* conf
Neighborhood Structure Configuration Models.
WWW
Felix I. Stamm, Michael Scholkemper, Michael T. Schaub, Markus Strohmaier
2022 Misc conf
Blind Extraction of Equitable Partitions from Graph Signals.
ICASSP
Michael Scholkemper, Michael T. Schaub
2022 J jnl
Blind Extraction of Equitable Partitions from Graph Signals.
CoRR
Michael Scholkemper, Michael T. Schaub
2022 J jnl
Neighborhood Structure Configuration Models.
CoRR
Felix I. Stamm, Michael Scholkemper, Markus Strohmaier, Michael T. Schaub
2021 J jnl
Local, global and scale-dependent node roles.
CoRR
Michael Scholkemper, Michael T. Schaub