mlsanityData to 7 Oct 2026

Torsional Diffusion for Molecular Conformer Generation

arXiv 2206.01729 ↗First posted 1 Jun 2022physics.chem-ph cs.LG q-bio.BMcited by 262

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Cited by 131 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Molecular conformer generation is a fundamental task in computational chemistry. Several machine learning approaches have been developed, but none have outperformed state-of-the-art cheminformatics methods. We propose torsional diffusion, a novel diffusion framework that operates on the space of torsion angles via a diffusion process on the hypertorus and an extrinsic-to-intrinsic score model. On a standard benchmark of drug-like molecules, torsional diffusion generates superior conformer ensembles compared to machine learning and cheminformatics methods in terms of both RMSD and chemical properties, and is orders of magnitude faster than previous diffusion-based models. Moreover, our model provides exact likelihoods, which we employ to build the first generalizable Boltzmann generator. Code is available at https://github.com/gcorso/torsional-diffusion.

Key facts. Cited by 262 papers in the map (data through 7 Oct 2026). Builds on 23 of its 64 references that are in the map. First posted on arXiv 1 Jun 2022.

Builds on

23 of 64 references.

References · 23

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  4. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  5. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  6. 2021E(n) Equivariant Graph Neural Networkscited by 951
  7. 2018Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point cloudscited by 735
  8. 2021E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentialscited by 701
  9. 2021Score-based Generative Modeling in Latent Spacecited by 634
  10. 2017SchNet: A continuous-filter convolutional neural network for modeling quantum interactionscited by 569
  11. 2022GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generationcited by 511
  12. 2020Learning from Protein Structure with Geometric Vector Perceptronscited by 308
11 more
  1. 2020GEOM: Energy-annotated molecular conformations for property prediction and molecular generationcited by 238
  2. 2022Riemannian Score-Based Generative Modellingcited by 216
  3. 2021Learning Gradient Fields for Molecular Conformation Generationcited by 162
  4. 2022EquiBind: Geometric Deep Learning for Drug Binding Structure Predictioncited by 143
  5. 2021GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensemblescited by 106
  6. 2021Learning Neural Generative Dynamics for Molecular Conformation Generationcited by 87
  7. 2019A Generative Model for Molecular Distance Geometrycited by 73
  8. 2022Subspace Diffusion Generative Modelscited by 70
  9. 2021An End-to-End Framework for Molecular Conformation Generation via Bilevel Programmingcited by 59
  10. 2021Smooth Normalizing Flowscited by 52
  11. 2021Bootstrap Your Flowcited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 25; 2023: 78; 2024: 69; 2025: 54; 2026: 36.

262 papers.

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  1. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
  2. 2022DiGress: Discrete Denoising diffusion for graph generationcited by 503
  3. 2022TabDDPM: Modelling Tabular Data with Diffusion Modelscited by 373
  4. 2022DiffusionDet: Diffusion Model for Object Detectioncited by 354
  5. 2024Retrieval-Augmented Generation for AI-Generated Content: A Surveycited by 352
  6. 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 307
  7. 2022A Survey on Generative Diffusion Modelcited by 238
  8. 2023SE(3) diffusion model with application to protein backbone generationcited by 214
  9. 2022Structure-based Drug Design with Equivariant Diffusion Modelscited by 213
  10. 2022An optimal control perspective on diffusion-based generative modelingcited by 145
  11. 2023Denoising Diffusion Samplerscited by 144
  12. 2023Crystal Structure Prediction by Joint Equivariant Diffusioncited by 142
38 more
  1. 2024Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Controlcited by 136
  2. 2023Equivariant flow matchingcited by 131
  3. 2022Flow Annealed Importance Sampling Bootstrapcited by 124
  4. 2022Equivariant 3D-Conditional Diffusion Models for Molecular Linker Designcited by 121
  5. 2022Uncovering the Disentanglement Capability in Text-to-Image Diffusion Modelscited by 116
  6. 2022Protein structure generation via folding diffusioncited by 113
  7. 2022Diffusion-based Molecule Generation with Informative Prior Bridgescited by 104
  8. 2023Improved sampling via learned diffusionscited by 103
  9. 2023A theory of continuous generative flow networkscited by 98
  10. 2023MatterGen: a generative model for inorganic materials designcited by 98
  11. 2023Reflected Diffusion Modelscited by 81
  12. 2023Generative Diffusion Models on Graphs: Methods and Applicationscited by 79
  13. 2025Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matchingcited by 78
  14. 2024Discrete-state Continuous-time Diffusion for Graph Generationcited by 73
  15. 2022Equivariant Energy-Guided SDE for Inverse Molecular Designcited by 72
  16. 2022HouseDiffusion: Vector Floorplan Generation via a Diffusion Model with Discrete and Continuous Denoisingcited by 72
  17. 2023Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamicscited by 72
  18. 2024An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimizationcited by 72
  19. 2022ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphscited by 69
  20. 2025Diffusion Language Models Know the Answer Before Decodingcited by 68
  21. 2023Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Modelscited by 65
  22. 2024Position: Topological Deep Learning is the New Frontier for Relational Learningcited by 65
  23. 2023EigenFold: Generative Protein Structure Prediction with Diffusion Modelscited by 63
  24. 2023Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamicscited by 62
  25. 2023Diffusion Models for Constrained Domainscited by 60
  26. 2023Swallowing the Bitter Pill: Simplified Scalable Conformer Generationcited by 55
  27. 2024Feedback Efficient Online Fine-Tuning of Diffusion Modelscited by 52
  28. 2023Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generationcited by 50
  29. 2023InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Modelscited by 48
  30. 2024Improved off-policy training of diffusion samplerscited by 47
  31. 2024Sequential Controlled Langevin Diffusionscited by 47
  32. 2023Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generationcited by 46
  33. 2023Graph Denoising Diffusion for Inverse Protein Foldingcited by 44
  34. 2024Transferable Boltzmann Generatorscited by 43
  35. 2024ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generationcited by 41
  36. 20233D molecule generation by denoising voxel gridscited by 38
  37. 2023Mirror Diffusion Models for Constrained and Watermarked Generationcited by 38
  38. 2023SE(3) Equivariant Augmented Coupling Flowscited by 37

50 most cited of 262 All 262 (JSON)