riemannian manifold

Riemannian Convex Potential Maps ICML 2021 Riemannian Embedding Banks for Common Spatial Patterns with EEG-based SPD Neural Networks AAAI 2021 Shadow Manifold Hamiltonian Monte Carlo AISTATS 2021 Unitary Branching Programs: Learnability and Lower Bounds ICML 2021 Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels NeurIPS 2021 Differentiating through the Fréchet Mean ICML 2020 DyERNIE: Dynamic Evolution of Riemannian Manifold Embeddings for Temporal Knowledge Graph Completion EMNLP 2020 Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems L4DC 2020 Evaluating Natural Alpha Embeddings on Intrinsic and Extrinsic Tasks ACL 2020 From Nesterov’s Estimate Sequence to Riemannian Acceleration COLT 2020 High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds NeurIPS 2020 Learning Flat Latent Manifolds with VAEs ICML 2020 Learning Weighted Submanifolds With Variational Autoencoders and Riemannian Variational Autoencoders CVPR 2020 Matérn Gaussian Processes on Riemannian Manifolds NeurIPS 2020 Mixed-curvature Variational Autoencoders ICLR 2020 Riemannian Continuous Normalizing Flows NeurIPS 2020 Synchronizing Probability Measures on Rotations via Optimal Transport CVPR 2020 Variational Autoencoders with Riemannian Brownian Motion Priors ICML 2020 Wasserstein Control of Mirror Langevin Monte Carlo COLT 2020 Bayesian Optimization Meets Riemannian Manifolds in Robot Learning CoRL 2019 Efficiently escaping saddle points on manifolds NeurIPS 2019 Escaping from saddle points on Riemannian manifolds NeurIPS 2019 Fast and Robust Shortest Paths on Manifolds Learned from Data AISTATS 2019 Hyperbolic Graph Neural Networks NeurIPS 2019 On the Curved Geometry of Accelerated Optimization NeurIPS 2019