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Hyperbolic Disk Embeddings for Directed Acyclic GraphsPreprint

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Fully Hyperbolic Graph Convolution Network for Recommendation

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Scalable Hyperbolic Recommender SystemsPreprint

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Embedding Heterogeneous Networks into Hyperbolic Space Without Meta-path

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Poincaré Wasserstein AutoencoderPreprint

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Probing BERT in Hyperbolic SpacesPreprint

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Riemannian Stochastic Recursive Gradient Algorithm

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Learning to Optimize on SPD Manifolds

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R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with Curvature Independent RatePreprint

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Scalable and Effective Temporal Graph Representation Learning With Hyperbolic Geometry

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A Multi-Sensor Fusion Underwater Localization Method Based on Unscented Kalman Filter on Manifolds

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HSR: Hyperbolic Social Recommender

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Hierarchical Metadata-Aware Document Categorization under Weak Supervision

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Stochastic Zeroth-Order Riemannian Derivative Estimation and Optimization

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Escaping from saddle points on Riemannian manifoldsPreprint

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HyperML: A Boosting Metric Learning Approach in Hyperbolic Space for Recommender SystemsPreprint

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Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)

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Multimodal sentiment and emotion recognition in hyperbolic space

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Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification

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Supervised LogEuclidean Metric Learning for Symmetric Positive Definite MatricesPreprint

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Understanding symmetries in deep networksPreprint

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Skip-gram word embeddings in hyperbolic spacePreprint

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Optimizing Oblique Projections for Nonlinear Systems using Trajectories

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CO-SNE: Dimensionality Reduction and Visualization for Hyperbolic Data

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The Euclidean Space is Evil: Hyperbolic Attribute Editing for Few-shot Image Generation

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Gradient descent in hyperbolic spacePreprint

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McTorch, a manifold optimization library for deep learningPreprint

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Computation for Latent Variable Model Estimation: A Unified Stochastic Proximal Framework

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Hyperbolic Music Transformer for Structured Music Generation

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Tag2Vec: Learning Tag Representations in Tag Networks

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Inferring Concept Hierarchies from Text Corpora via Hyperbolic EmbeddingsPreprint

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Stochastic Approximation for Optimization in Shape Spaces

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Constrained Stochastic Gradient Descent: The Good Practice

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Variational Bayes on manifolds

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PERFECT: A Hyperbolic Embedding for Joint User and Community Alignment

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Orthogonal Deep Neural NetworksPreprint

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An Intrinsic Cramér-Rao Bound on Lie Groups

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On Faster Convergence of Scaled Sign Gradient Descent

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HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning

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Similarity Distance Learning on SPD Manifold for Writer Independent Offline Signature Verification

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Minimum Stein Discrepancy EstimatorsPreprint

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Sequential Quadratic Optimization for Nonlinear Optimization Problems on Riemannian Manifolds

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Multi-hop Knowledge Graph Reasoning Based on Hyperbolic Knowledge Graph Embedding and Reinforcement Learning

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Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech Processing

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HYPER2: Hyperbolic embedding for hyper-relational link prediction

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Learning to Optimize on Riemannian Manifolds

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RicciNet: Deep Clustering via A Riemannian Generative Model

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Geometry, Manifolds, and Nonconvex Optimization: How Geometry Can Help Optimization

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HyperKG: Hyperbolic Knowledge Graph Embeddings for Knowledge Base CompletionPreprint

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Improved Variance Reduction Methods for Riemannian Non-Convex Optimization

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Designing universal causal deep learning models: The geometric (Hyper)transformer

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Hyperbolic Neural Network-Based Preselection for Expensive Multiobjective Optimization

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Multi-Facet Recommender Networks with Spherical Optimization

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HiG2Vec: hierarchical representations of Gene Ontology and genes in the Poincaré ball

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Universal Approximation Theorems for Differentiable Geometric Deep LearningPreprint

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Enhancing Recommendation with Automated Tag Taxonomy Construction in Hyperbolic Space

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Quantization and clustering on Riemannian manifolds with an application to air traffic analysis

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Grassmannian learning mutual subspace method for image set recognition

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RMAML: Riemannian meta-learning with orthogonality constraints

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Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincaré Ball

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Learning Co-Sparse Analysis Operators With Separable Structures

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Hyperbolic node embedding for signed networks

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Leveraging Hyperbolic Dynamic Neural Networks for Knowledge-Aware Recommendation

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Adaptive Log-Euclidean Metrics for SPD Matrix Learning

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Intrinsic Grassmann Averages for Online Linear, Robust and Nonlinear Subspace Learning

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A Riemannian optimization approach to the radial distribution network load flow problem

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Curvature of the Manifold of Fixed-Rank Positive-Semidefinite Matrices Endowed with the Bures–Wasserstein Metric

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Projection-free nonconvex stochastic optimization on Riemannian manifolds

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Handling the Positive-Definite Constraint in the Bayesian Learning RulePreprint

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Hyperbolic Busemann Learning with Ideal PrototypesPreprint

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Parameter identification of vertical plane model for autonomous underwater vehicle based on hierarchical multi-innovation stochastic gradient algorithm

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Neural Natural Logic Inference for Interpretable Question Answering

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Populations of unlabelled networks: graph space geometry and generalized geodesic principal components

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Stochastic Approximation on Riemannian Manifolds

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Symmetry-invariant optimization in deep networksPreprint

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SKYPER: Legal case retrieval via skeleton-aware hypergraph embedding in the hyperbolic space

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An Optimization Method in the Random Switching Frequency SVPWM for the Sideband Harmonic Dispersion

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Hyperbolic Contrastive Learning for Cross-Domain Recommendation

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Riemannian stochastic variance reduced gradientPreprint

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Riemannian stochastic variance reduced gradient on Grassmann manifoldPreprint

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Riemannian Stochastic Variance Reduced Gradient Algorithm with Retraction and Vector Transport

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