mlsanityData to 7 Oct 2026

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming

arXiv 2105.07246 ↗First posted 15 May 2021cs.LG q-bio.BMcited by 59

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Abstract (arXiv)

Predicting molecular conformations (or 3D structures) from molecular graphs is a fundamental problem in many applications. Most existing approaches are usually divided into two steps by first predicting the distances between atoms and then generating a 3D structure through optimizing a distance geometry problem. However, the distances predicted with such two-stage approaches may not be able to consistently preserve the geometry of local atomic neighborhoods, making the generated structures unsatisfying. In this paper, we propose an end-to-end solution for molecular conformation prediction called ConfVAE based on the conditional variational autoencoder framework. Specifically, the molecular graph is first encoded in a latent space, and then the 3D structures are generated by solving a principled bilevel optimization program. Extensive experiments on several benchmark data sets prove the effectiveness of our proposed approach over existing state-of-the-art approaches. Code is available at https://github.com/MinkaiXu/ConfVAE-ICML21

Key facts. Cited by 59 papers in the map (data through 7 Oct 2026). Builds on 27 of its 57 references that are in the map. First posted on arXiv 15 May 2021.

Builds on

27 of 57 references.

References · 27

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  3. 2018How Powerful are Graph Neural Networks?cited by 4,355
  4. 2013Auto-Encoding Variational Bayescited by 3,980
  5. 2018Neural Ordinary Differential Equationscited by 3,733
  6. 2017Neural Message Passing for Quantum Chemistrycited by 3,460
  7. 2013Spectral Networks and Locally Connected Networks on Graphscited by 1,097
  8. 2019Strategies for Pre-training Graph Neural Networkscited by 964
  9. 2015Convolutional Networks on Graphs for Learning Molecular Fingerprintscited by 751
  10. 2017SchNet: A continuous-filter convolutional neural network for modeling quantum interactionscited by 569
  11. 2018Bilevel Programming for Hyperparameter Optimization and Meta-Learningcited by 403
  12. 2018Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generationcited by 363
15 more
  1. 2015Gradient-based Hyperparameter Optimization through Reversible Learningcited by 357
  2. 2020GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generationcited by 301
  3. 2016Molecular Graph Convolutions: Moving Beyond Fingerprintscited by 238
  4. 2020GEOM: Energy-annotated molecular conformations for property prediction and molecular generationcited by 238
  5. 2017Forward and Reverse Gradient-Based Hyperparameter Optimizationcited by 232
  6. 2017Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimizationcited by 188
  7. 2019Symmetry-adapted generation of 3d point sets for the targeted discovery of moleculescited by 171
  8. 2019Molecular geometry prediction using a deep generative graph neural networkcited by 91
  9. 2021Learning Neural Generative Dynamics for Molecular Conformation Generationcited by 87
  10. 2020A Graph to Graphs Framework for Retrosynthesis Predictioncited by 85
  11. 2019A Generative Model for Molecular Distance Geometrycited by 73
  12. 2020Symmetry-Aware Actor-Critic for 3D Molecular Designcited by 55
  13. 2020Reinforcement Learning for Molecular Design Guided by Quantum Mechanicscited by 51
  14. 2019Generating valid Euclidean distance matricescited by 19
  15. 2020TorsionNet: A Reinforcement Learning Approach to Sequential Conformer Searchcited by 15

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Citing papers per year: 2021: 4; 2022: 17; 2023: 14; 2024: 14; 2025: 8; 2026: 2.

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  1. 2022Equivariant Diffusion for Molecule Generation in 3Dcited by 666
  2. 2022GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generationcited by 511
  3. 2022Torsional Diffusion for Molecular Conformer Generationcited by 262
  4. 2022Equivariant 3D-Conditional Diffusion Models for Molecular Linker Designcited by 121
  5. 2022Generating 3D Molecules for Target Protein Bindingcited by 104
  6. 2022Diffusion-based Molecule Generation with Informative Prior Bridgescited by 104
  7. 2021Inverse design of 3d molecular structures with conditional generative neural networkscited by 93
  8. 2022MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Designcited by 66
  9. 2022MDM: Molecular Diffusion Model for 3D Molecule Generationcited by 58
  10. 2022DiffBP: Generative Diffusion of 3D Molecules for Target Protein Bindingcited by 58
  11. 2023Swallowing the Bitter Pill: Simplified Scalable Conformer Generationcited by 55
  12. 2022Graph-based Molecular Representation Learningcited by 51
38 more
  1. 2023Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltoniancited by 38
  2. 20223DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Designcited by 33
  3. 2021Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphscited by 31
  4. 2022Direct Molecular Conformation Generationcited by 30
  5. 2023Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaborationcited by 30
  6. 2024A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applicationscited by 28
  7. 2022Gradient-based Bi-level Optimization for Deep Learning: A Surveycited by 26
  8. 2023Towards Symmetry-Aware Generation of Periodic Materialscited by 25
  9. 2022DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulationscited by 24
  10. 2022Generative Coarse-Graining of Molecular Conformationscited by 21
  11. 2022Graph Neural Networks for Moleculescited by 21
  12. 2024MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworkscited by 15
  13. 2023Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular Dynamicscited by 14
  14. 2024Geometric Trajectory Diffusion Modelscited by 13
  15. 2023DiffSDS: A language diffusion model for protein backbone inpainting under geometric conditions and constraintscited by 10
  16. 2023Deep Learning Methods for Small Molecule Drug Discovery: A Surveycited by 10
  17. 2023An Equivariant Generative Framework for Molecular Graph-Structure Co-Designcited by 10
  18. 2024Weisfeiler Leman for Euclidean Equivariant Machine Learningcited by 10
  19. 2024Geometry Informed Tokenization of Molecules for Language Model Generationcited by 10
  20. 2024Molecular relaxation by reverse diffusion with time step predictioncited by 9
  21. 2023Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation?cited by 8
  22. 2023PrefixMol: Target- and Chemistry-aware Molecule Design via Prefix Embeddingcited by 7
  23. 2023CoarsenConf: Equivariant Coarsening with Aggregated Attention for Molecular Conformer Generationcited by 7
  24. 2021Augmenting Molecular Deep Generative Models with Topological Data Analysis Representationscited by 6
  25. 2025Sampling 3D Molecular Conformers with Diffusion Transformerscited by 5
  26. 2024SubGDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learningcited by 4
  27. 2024WGFormer: An SE(3)-Transformer Driven by Wasserstein Gradient Flows for Molecular Ground-State Conformation Predictioncited by 4
  28. 2025Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflowcited by 4
  29. 2024EquiFlow: Equivariant Conditional Flow Matching with Optimal Transport for 3D Molecular Conformation Predictioncited by 3
  30. 2025Recent Developments in GNNs for Drug Discoverycited by 3
  31. 2026Geometric Flow Matching for Molecular Conformation Generation via Manifold Decompositioncited by 3
  32. 2022Thermal half-lives of azobenzene derivatives: virtual screening based on intersystem crossing using a machine learning potentialcited by 2
  33. 2023Molecular Conformation Generation via Shifting Scorescited by 2
  34. 2024Equivariant Blurring Diffusion for Hierarchical Molecular Conformer Generationcited by 2
  35. 2025HybridLinker: Topology-Guided Posterior Sampling for Enhanced Diversity and Validity in 3D Molecular Linker Generationcited by 2
  36. 20233D Molecular Geometry Analysis with 2D Graphscited by 1
  37. 2024REBIND: Enhancing ground-state molecular conformation via force-based graph rewiringcited by 1
  38. 2024Riemannian Denoising Model for Molecular Structure Optimization with Chemical Accuracycited by 1

50 most cited of 59 All 59 (JSON)