QM9

QM9 is a dataset that contains molecular structures and their corresponding properties, used to evaluate machine learning models in predicting molecular characteristics.

Papers using QM9 (78)

DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules2025 · 38 citesLearning-Order Autoregressive Models with Application to Molecular Graph Generation2025 · 20 citesRegression with Large Language Models for Materials and Molecular Property Prediction2024 · 8 citesQuantum mechanical dataset of 836k neutral closed shell molecules with upto 5 heavy atoms from CNOFSiPSClBr2024 · 7 citesAll-atom Diffusion Transformers: Unified generative modelling of molecules and materials2025 · 5 citesGuiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation2025 · 4 citesA Reinforcement Learning-Driven Transformer GAN for Molecular Generation2025 · 4 citesClifford Group Equivariant Diffusion Models for 3D Molecular Generation2025 · 3 citesQUIVER: Quantum-Informed Views for Enhanced Representations in Large ML Models2026AIM: Adaptive Intervention for Deep Multi-task Learning of Molecular Properties2025 · 2 citesActive Deep Kernel Learning of Molecular Properties: Realizing Dynamic Structural Embeddings2024 · 3 citesTriplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers2024 · 3 citesTransport-Coupled Bayesian Flows for Molecular Graph Generation2025 · 1 citesFrame-based Equivariant Diffusion Models for 3D Molecular Generation2025 · 1 citesUncertainty Quantification in Graph Neural Networks with Shallow Ensembles2025 · 1 citesGeometric Representation Condition Improves Equivariant Molecule Generation2024 · 1 citesGenerative Pseudo-Force Fields for Molecular Generation2026Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics2026Same Graph, Different Likelihoods: Calibration of Autoregressive Graph Generators via Permutation-Equivalent Encodings2026MolPaQ: Modular Quantum-Classical Patch Learning for Interpretable Molecular Generation2026Surrogate Functionals for Machine-Learned Orbital-Free Density Functional Theory2026Enhancing Molecular Property Predictions by Learning from Bond Modelling and Interactions2026Bayesian Optimization in Chemical Compound Sub-Spaces using Low-Dimensional Molecular Descriptors2026Information Routing in Atomistic Foundation Models: How Task Alignment and Equivariance Shape Linear Disentanglement2026VecMol: Vector-Field Representations for 3D Molecule Generation2026Permutation-Symmetrized Diffusion for Unconditional Molecular Generation2026Autotuning T-PaiNN: Enabling Data-Efficient GNN Interatomic Potential Development via Classical-to-Quantum Transfer Learning2026Hierarchy-Guided Topology Latent Flow for Molecular Graph Generation2026Impact of Local Descriptors Derived from Machine Learning Potentials in Graph Neural Networks for Molecular Property Prediction2026Efficient, Equivariant Predictions of Distributed Charge Models2026Multi-objective optimization and quantum hybridization of equivariant deep learning interatomic potentials on organic and inorganic compounds2026Quantized SO(3)-Equivariant Graph Neural Networks for Efficient Molecular Property Prediction2026Molecular electrostatic potentials from machine learning models for dipole and quadrupole predictions2026Constraint-Aware Neurosymbolic Uncertainty Quantification with Bayesian Deep Learning for Scientific Discovery2026PCEvo: Path-Consistent Molecular Representation via Virtual Evolutionary2026qs$GW$ quasiparticle and $GW$-BSE excitation energies of 133,885 molecules2025MolSculpt: Sculpting 3D Molecular Geometries from Chemical Syntax2025MolGuidance: Advanced Guidance Strategies for Conditional Molecular Generation with Flow Matching2025Mamba-driven multi-perspective structural understanding for molecular ground-state conformation prediction2025VEDA: 3D Molecular Generation via Variance-Exploding Diffusion with Annealing2025Power law attention biases for molecular transformers2025FlexiFlow: decomposable flow matching for generation of flexible molecular ensemble2025Beyond Atoms: Evaluating Electron Density Representation for 3D Molecular Learning2025Spectral Analysis of Molecular Kernels: When Richer Features Do Not Guarantee Better Generalization2025Layer-to-Layer Knowledge Mixing in Graph Neural Network for Chemical Property Prediction2025InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames2025Quantum Graph Attention Networks: Trainable Quantum Encoders for Inductive Graph Learning2025Fast and Interpretable Machine Learning Modelling of Atmospheric Molecular Clusters2025MolMark: Safeguarding Molecular Structures through Learnable Atom-Level Watermarking2025Rotational Sampling: A Plug-and-Play Encoder for Rotation-Invariant 3D Molecular GNNs2025GeoRecon: Graph-Level Representation Learning for 3D Molecules via Reconstruction-Based Pretraining2025MuAPBEK: An Improved Analytical Kinetic Energy Density Functional for Quantum Chemistry2025Equivariant Spherical Transformer for Efficient Molecular Modeling2025Stable and Accurate Orbital-Free DFT Powered by Machine Learning2025Towards Unified and Lossless Latent Space for 3D Molecular Latent Diffusion Modeling2025Inductive Graph Representation Learning with Quantum Graph Neural Networks2025Riemannian Denoising Model for Molecular Structure Optimization with Chemical Accuracy2024Learning Equivariant Non-Local Electron Density Functionals2024MGNN: Moment Graph Neural Network for Universal Molecular Potentials2024Hybrid quantum cycle generative adversarial network for small molecule generation2024 · 21 citesActive Causal Learning for Decoding Chemical Complexities with Targeted Interventions2024 · 7 citesEquiFlow: Equivariant Conditional Flow Matching with Optimal Transport for 3D Molecular Conformation Prediction2024 · 4 citesUnified Generative Modeling of 3D Molecules via Bayesian Flow Networks2024 · 3 citesEfficient molecular conformation generation with quantum-inspired algorithm2024 · 3 citesAdaptive hybrid density functionals2024 · 2 citesGaussian Plane-Wave Neural Operator for Electron Density Estimation2024 · 1 citesClassifier-free graph diffusion for molecular property targeting2023Adaptive atomic basis sets2024Data-Efficient Molecular Generation with Hierarchical Textual Inversion2024SE3Set: Harnessing equivariant hypergraph neural networks for molecular representation learning2024In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphs2024FreeCG: Free the Design Space of Clebsch-Gordan Transform for Machine Learning Force Fields2024Distribution Learning for Molecular Regression2024Hessian QM9: A quantum chemistry database of molecular Hessians in implicit solvents2024XMOL: Explainable Multi-property Optimization of Molecules2024Efficient Sampling for Machine Learning Electron Density and Its Response in Real Space2024Deconstructing equivariant representations in molecular systems2024GUISE: Graph GaUssIan Shading watErmark2024