QM9

Dataset Card for "QM9" More Information needed

Papers using QM9 (27)

Inductive Graph Representation Learning with Quantum Graph Neural Networks2025Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs2022 · 65 citesGeometry-Complete Diffusion for 3D Molecule Generation and Optimization2023 · 7 citesFAENet: Frame Averaging Equivariant GNN for Materials Modeling2023 · 7 citesScaling Spherical CNNs2023 · 6 citesMolecular Geometry-aware Transformer for accurate 3D Atomic System modeling2023 · 3 citesTriplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers2024 · 3 citesNeuralNEB -- Neural Networks can find Reaction Paths Fast2022 · 2 citesAn Unpooling Layer for Graph Generation2022 · 1 citesPointGAT: A quantum chemical property prediction model integrating graph attention and 3D geometry2023 · 1 citesTraining speedups via batching for geometric learning: an analysis of static and dynamic algorithms2025 · 1 citesDistance-Geometric Graph Attention Network (DG-GAT) for 3D Molecular Geometry2022On the Interplay of Subset Selection and Informed Graph Neural Networks2023E(n) Equivariant Topological Neural Networks2024SE3Set: Harnessing equivariant hypergraph neural networks for molecular representation learning2024In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphs2024Learning Equivariant Non-Local Electron Density Functionals2024Uncertainty Quantification in Graph Neural Networks with Shallow Ensembles2025Equivariant Spherical Transformer for Efficient Molecular Modeling2025Rotational Sampling: A Plug-and-Play Encoder for Rotation-Invariant 3D Molecular GNNs2025Quantum Graph Attention Networks: Trainable Quantum Encoders for Inductive Graph Learning2025Layer-to-Layer Knowledge Mixing in Graph Neural Network for Chemical Property Prediction2025Connectivity-Guided Sparsification of 2-FWL GNNs: Preserving Full Expressivity with Improved Efficiency2025Quantized SO(3)-Equivariant Graph Neural Networks for Efficient Molecular Property Prediction2026Autotuning T-PaiNN: Enabling Data-Efficient GNN Interatomic Potential Development via Classical-to-Quantum Transfer Learning2026How Embeddings Shape Graph Neural Networks: Classical vs Quantum-Oriented Node Representations2026DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules2025