Title
Oversmoothing, "Oversquashing", Heterophily, Long-Range, and more: Demystifying Common Beliefs in Graph Machine Learning Adrian Arnaiz-Rodriguez Federico Errica AI4CE 16 0 0 21 May 2025
Pretraining Graph Transformers with Atom-in-a-Molecule Quantum Properties for Improved ADMET Modeling Alessio Fallani Ramil I. Nugmanov Jose A. Arjona-Medina Jörg Kurt Wegner Alexandre Tkatchenko Kostiantyn Chernichenko MedIm AI4CE 39 0 0 10 Oct 2024
Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization Dingshuo Chen Zhixun Li Yuyan Ni Guibin Zhang Ding Wang Qiang Liu Shu Wu Jeffrey Xu Yu Liang Wang 54 4 0 02 Sep 2024
TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs J. Gastinger Shenyang Huang Mikhail Galkin Erfan Loghmani Ali Parviz ... Emanuele Rossi Ioannis Koutis Heiner Stuckenschmidt Reihaneh Rabbany Guillaume Rabusseau 48 7 0 14 Jun 2024
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning Shikun Feng Yuyan Ni Minghao Li Yanwen Huang Zhiming Ma Wei-Ying Ma Yanyan Lan SSL 58 7 0 15 May 2024
$$\texttt{MiniMol}$: A Parameter-Efficient Foundation Model for Molecular Learning$ $\texttt{MiniMol}$ : A Parameter-Efficient Foundation Model for Molecular Learning Kerstin Klaser Bla.zej Banaszewski S. Maddrell-Mander Callum McLean Luis Muller Alipanah Parviz Shenyang Huang Andrew Fitzgibbon AI4CE 53 5 0 23 Apr 2024
On the Scalability of GNNs for Molecular Graphs Maciej Sypetkowski Frederik Wenkel Farimah Poursafaei Nia Dickson Karush Suri Philip Fradkin Dominique Beaini GNN AI4CE 47 13 0 17 Apr 2024
DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models Nastaran Saadati Minh Pham Nasla Saleem Joshua R. Waite Aditya Balu Zhanhong Jiang Chinmay Hegde Soumik Sarkar MoMe 49 1 0 11 Apr 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 Hvilshoj Bla.zej Banaszewski Carlo Luschi Andrew William Fitzgibbon 43 3 0 06 Feb 2024
Position: Graph Foundation Models are Already Here Haitao Mao Zhikai Chen Wenzhuo Tang Jianan Zhao Yao Ma Tong Zhao Neil Shah Mikhail Galkin Jiliang Tang AI4CE 69 28 0 03 Feb 2024
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark Jan Tonshoff Martin Ritzert Eran Rosenbluth Martin Grohe 28 47 0 01 Sep 2023
Context-enriched molecule representations improve few-shot drug discovery Johannes Schimunek Philipp Seidl Lukas Friedrich Daniel Kuhn F. Rippmann Sepp Hochreiter Günter Klambauer 58 26 0 24 Apr 2023
A Systematic Survey of Chemical Pre-trained Models Jun Xia Yanqiao Zhu Yuanqi Du Stan Z.Li AI4CE 61 51 0 29 Oct 2022
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking Gabriele Corso Hannes Stärk Bowen Jing Regina Barzilay Tommi Jaakkola DiffM 142 412 0 04 Oct 2022
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials Peter K. Eastman P. Behara David L. Dotson Raimondas Galvelis John E. Herr ... J. Chodera Benjamin P. Pritchard Yuanqing Wang Gianni De Fabritiis T. Markland 51 105 0 21 Sep 2022
Graph Neural Networks with Learnable Structural and Positional Representations Vijay Prakash Dwivedi A. Luu T. Laurent Yoshua Bengio Xavier Bresson GNN 197 312 0 15 Oct 2021
The Open Catalyst 2020 (OC20) Dataset and Community Challenges L. Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi ... Brandon M. Wood Junwoong Yoon Devi Parikh C. L. Zitnick Zachary W. Ulissi 232 505 0 20 Oct 2020
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 189 918 0 02 Mar 2020
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 257 1,787 0 02 Mar 2017