Poursafaei, Farimah

9 publications

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

NeurIPS 2024 On the Scalability of GNNs for Molecular Graphs Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini

ICLRW 2024 On the Scalability of GNNs for Molecular Graphs Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini

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

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