Huang, Shenyang

11 publications

ICLR 2025 ContextGNN: Beyond Two-Tower Recommendation Systems Yiwen Yuan, Zecheng Zhang, Xinwei He, Akihiro Nitta, Weihua Hu, Manan Shah, Blaž Stojanovič, Shenyang Huang, Jan Eric Lenssen, Jure Leskovec, Matthias Fey

NeurIPS 2025 MiNT: Multi-Network Transfer Benchmark for Temporal Graph Learning Kiarash Shamsi, Tran Gia Bao Ngo, Razieh Shirzadkhani, Shenyang Huang, Farimah Poursafaei, Poupak Azad, Reihaneh Rabbany, Baris Coskunuzer, Guillaume Rabusseau, Cuneyt Gurcan Akcora

LoG 2025 UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs Shenyang Huang, Farimah Poursafaei, Reihaneh Rabbany, Guillaume Rabusseau, Emanuele Rossi

ICLR 2024 GraphPulse: Topological Representations for Temporal Graph Property Prediction Kiarash Shamsi, Farimah Poursafaei, Shenyang Huang, Bao Tran Gia Ngo, Baris Coskunuzer, Cuneyt Gurcan Akcora

ICMLW 2024 MiniMol: A Parameter-Efficient Foundation Model for Molecular Learning Kerstin Klaser, Blazej Banaszewski, Samuel Maddrell-Mander, Callum McLean, Luis Müller, Ali Parviz, Shenyang Huang, Andrew W Fitzgibbon

NeurIPS 2024 TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs Julia Gastinger, Shenyang Huang, Mikhail Galkin, Erfan Loghmani, Ali Parviz, Farimah Poursafaei, Jacob Danovitch, Emanuele Rossi, Ioannis Koutis, Heiner Stuckenschmidt, Reihaneh Rabbany, Guillaume Rabusseau

ICMLW 2024 Temporal Graph Rewiring with Expander Graphs Katarina Petrović, Shenyang Huang, Farimah Poursafaei, Petar Veličković

ICLR 2024 Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michał Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters

TMLR 2023 GPS++: Reviving the Art of Message Passing for Molecular Property Prediction Dominic Masters, Josef Dean, Kerstin Klaeser, Zhiyi Li, Samuel Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Andrew W Fitzgibbon, Shenyang Huang, Ladislav Rampášek, Dominique Beaini

NeurIPS 2023 Temporal Graph Benchmark for Machine Learning on Temporal Graphs Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael Bronstein, Guillaume Rabusseau, Reihaneh Rabbany

NeurIPS 2022 Towards Better Evaluation for Dynamic Link Prediction Farimah Poursafaei, Shenyang Huang, Kellin Pelrine, Reihaneh Rabbany