mlsanityData to 7 Oct 2026

Geoopt: Riemannian Optimization in PyTorch

arXiv 2005.02819 ↗First posted 6 May 2020cs.CG cs.LGcited by 109

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Abstract (arXiv)

Geoopt is a research-oriented modular open-source package for Riemannian Optimization in PyTorch. The core of Geoopt is a standard Manifold interface that allows for the generic implementation of optimization algorithms. Geoopt supports basic Riemannian SGD as well as adaptive optimization algorithms. Geoopt also provides several algorithms and arithmetic methods for supported manifolds, which allow composing geometry-aware neural network layers that can be integrated with existing models.

Key facts. Cited by 109 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 May 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 12; 2022: 15; 2023: 16; 2024: 22; 2025: 30; 2026: 14.

109 papers.

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  1. 2021Hyperbolic Deep Neural Networks: A Surveycited by 138
  2. 2021Fully Hyperbolic Neural Networkscited by 107
  3. 2025OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fittingcited by 94
  4. 2023Hyperbolic Deep Learning in Computer Vision: A Surveycited by 72
  5. 2024Fisher Flow Matching for Generative Modeling over Discrete Datacited by 68
  6. 2022SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEGcited by 53
  7. 2021Learning the Predictability of the Futurecited by 48
  8. 2023Fully Hyperbolic Convolutional Neural Networks for Computer Visioncited by 48
  9. 2022The Numerical Stability of Hyperbolic Representation Learningcited by 46
  10. 2023HYperbolic Self-Paced Learning for Self-Supervised Skeleton-based Action Representationscited by 42
  11. 2021Tangent Space Backpropagation for 3D Transformation Groupscited by 40
  12. 2024Language Models as Hierarchy Encoderscited by 26
38 more
  1. 2024Hyperbolic Fine-Tuning for Large Language Modelscited by 24
  2. 2021Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approachcited by 23
  3. 2022Generalized Laplacian Positional Encoding for Graph Representation Learningcited by 21
  4. 2023A Survey of Geometric Optimization for Deep Learning: From Euclidean Space to Riemannian Manifoldcited by 21
  5. 2025Fg-T2M++: LLMs-Augmented Fine-Grained Text Driven Human Motion Generationcited by 21
  6. 2024Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structurescited by 20
  7. 2025Hyperbolic Deep Learning for Foundation Models: A Surveycited by 20
  8. 2022Contrastive Multi-view Hyperbolic Hierarchical Clusteringcited by 19
  9. 2023Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signalscited by 19
  10. 2022Rethinking the compositionality of point clouds through regularization in the hyperbolic spacecited by 18
  11. 2022Graph Neural Networks on SPD Manifolds for Motor Imagery Classification: A Perspective from the Time-Frequency Analysiscited by 15
  12. 2023Contrastive Graph Clustering in Curvature Spacescited by 15
  13. 2023Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learningcited by 15
  14. 2021HyperExpan: Taxonomy Expansion with Hyperbolic Representation Learningcited by 14
  15. 2021Extracting Event Temporal Relations via Hyperbolic Geometrycited by 13
  16. 2024HyperVQ: MLR-based Vector Quantization in Hyperbolic Spacecited by 13
  17. 2022Riemannian Hamiltonian methods for min-max optimization on manifoldscited by 12
  18. 2022Small Transformers Compute Universal Metric Embeddingscited by 12
  19. 2024Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wassersteincited by 12
  20. 2024SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEGcited by 12
  21. 2025HyperCore: The Core Framework for Building Hyperbolic Foundation Models with Comprehensive Modulescited by 12
  22. 2022Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text Classificationcited by 11
  23. 2022Deep Riemannian Networks for End-to-End EEG Decodingcited by 11
  24. 2025Geo-Sign: Hyperbolic Contrastive Regularisation for Geometrically Aware Sign Language Translationcited by 11
  25. 2023Dynamic Hyperbolic Attention Network for Fine Hand-object Reconstructioncited by 10
  26. 2022Bringing motion taxonomies to continuous domains via GPLVM on hyperbolic manifoldscited by 9
  27. 2025SECA: Semantically Equivalent and Coherent Attacks for Eliciting LLM Hallucinationscited by 9
  28. 2024HyperSDFusion: Bridging Hierarchical Structures in Language and Geometry for Enhanced 3D Text2Shape Generationcited by 8
  29. 2024Taxonomy-Aware Continual Semantic Segmentation in Hyperbolic Spaces for Open-World Perceptioncited by 8
  30. 2024HVT: A Comprehensive Vision Framework for Learning in Non-Euclidean Spacecited by 8
  31. 2022Autoencoding Hyperbolic Representation for Adversarial Generationcited by 7
  32. 2022NCVX: A General-Purpose Optimization Solver for Constrained Machine and Deep Learningcited by 7
  33. 2023GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learningcited by 7
  34. 2024A Riemannian Framework for Learning Reduced-order Lagrangian Dynamicscited by 7
  35. 2025Differentiable Generalized Sliced Wasserstein Planscited by 7
  36. 2023HypLL: The Hyperbolic Learning Librarycited by 6
  37. 2023Hyperbolic Graph Diffusion Modelcited by 6
  38. 2025DenoiseRotator: Enhance Pruning Robustness for LLMs via Importance Concentrationcited by 6

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