Long Range Graph Benchmark. - Vijay Prakash Dwivedi; Ladislav Rampásek; Michael Galkin; Ali Parviz; Guy Wolf; Anh Tuan Luu; Dominique Beaini (NeurIPS, 2022)

Generalized Laplacian Positional Encoding for Graph Representation Learning. - Sohir Maskey; Ali Parviz; Maximilian Thiessen; Hannes Stärk; Ylli Sadikaj; Haggai Maron (CoRR, 2022)

Resource-Constrained Knowledge Diffusion Processes Inspired by Human Peer Learning. - Ehsan Beikihassan; Amy K. Hoover; Ioannis Koutis; Ali Parviz; Niloofar Aghaieabiane (ECAI, 2023)

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; et al. (CoRR, 2023)

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; et al. (ICLR, 2024)

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

Reducing the Cost of Quantum Chemical Data By Backpropagating Through Density Functional Theory. - Alexander Mathiasen; Hatem Helal; Paul Balanca; Adam Krzywaniak; Ali Parviz; Frederik Hvilshøj; Blazej Banaszewski; Carlo Luschi; Andrew William Fitzgibbon (CoRR, 2024)

MiniMol: A Parameter-Efficient Foundation Model for Molecular Learning. - Kerstin Kläser 001; Blazej Banaszewski; Samuel Maddrell-Mander; Callum McLean; Luis Müller; Ali Parviz; Shenyang Huang; Andrew W. Fitzgibbon (CoRR, 2024)

Best of Both Worlds: Advantages of Hybrid Graph Sequence Models. - Ali Behrouz; Ali Parviz; Mahdi Karami; Clayton Sanford; Bryan Perozzi; Vahab Mirrokni (CoRR, 2024)

Are Large Language Models Good Temporal Graph Learners? - Shenyang Huang; Ali Parviz; Emma Kondrup; Zachary Yang; Zifeng Ding; Michael M. Bronstein; Reihaneh Rabbany; Guillaume Rabusseau (CoRR, 2025)

Scalable and Cost-Efficient de Novo Template-Based Molecular Generation. - Piotr Gainski; Oussama Boussif; Andrei Rekesh; Dmytro Shevchuk; Ali Parviz; Mike Tyers; Robert A. Batey; Michal Koziarski (CoRR, 2025)