riemannian manifold

Gaussian Differential Privacy on Riemannian Manifolds NeurIPS 2023 Geometrically regularized autoencoders for non-Euclidean data ICLR 2023 Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds JMLR 2023 Learning Harmonic Molecular Representations on Riemannian Manifold ICLR 2023 Metropolis Sampling for Constrained Diffusion Models NeurIPS 2023 Minimizing Dynamic Regret on Geodesic Metric Spaces COLT 2023 Nonconvex stochastic scaled gradient descent and generalized eigenvector problems UAI 2023 Non-Euclidean Motion Planning with Graphs of Geodesically-Convex Sets RSS 2023 Online Optimization over Riemannian Manifolds JMLR 2023 Open Problem: Polynomial linearly-convergent method for g-convex optimization? COLT 2023 Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds NeurIPS 2023 Riemannian Local Mechanism for SPD Neural Networks AAAI 2023 Riemannian Metric Learning via Optimal Transport ICLR 2023 Riemannian Projection-free Online Learning NeurIPS 2023 Riemannian Residual Neural Networks NeurIPS 2023 When Locally Linear Embedding Hits Boundary JMLR 2023 Efficient Riemannian Meta-Optimization by Implicit Differentiation AAAI 2022 Efficient Sampling on Riemannian Manifolds via Langevin MCMC NeurIPS 2022 First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces NeurIPS 2022 Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis ICML 2022 Geodesic Self-Attention for 3D Point Clouds NeurIPS 2022 Learning Riemannian Stable Dynamical Systems via Diffeomorphisms CoRL 2022 Lifting Weak Supervision To Structured Prediction NeurIPS 2022 Nested Hyperbolic Spaces for Dimensionality Reduction and Hyperbolic NN Design CVPR 2022 Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold NeurIPS 2022