Geometry

Field Convolutions for Surface CNNs ICCV 2021 Framing RNN as a kernel method: A neural ODE approach NeurIPS 2021 Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic NeurIPS 2021 Geometric structure of graph Laplacian embeddings JMLR 2021 Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels CoRL 2021 Hierarchical Clustering in General Metric Spaces using Approximate Nearest Neighbors AISTATS 2021 How can classical multidimensional scaling go wrong? NeurIPS 2021 Hyperbolic Procrustes Analysis Using Riemannian Geometry NeurIPS 2021 Importance of Parasagittal Sensor Information in Tongue Motion Capture Through a Diphonic Analysis Interspeech 2021 Improved Coresets and Sublinear Algorithms for Power Means in Euclidean Spaces NeurIPS 2021 Keep Your Distance: Land Division With Separation IJCAI 2021 Learning 3D Dense Correspondence via Canonical Point Autoencoder NeurIPS 2021 Learning a Gradient-free Riemannian Optimizer on Tangent Spaces AAAI 2021 Learning Interaction Kernels for Agent Systems on Riemannian Manifolds ICML 2021 Learning Riemannian Manifolds for Geodesic Motion Skills RSS 2021 Linear Bandits on Uniformly Convex Sets JMLR 2021 Link Prediction with Persistent Homology: An Interactive View ICML 2021 Localization in the Crowd with Topological Constraints AAAI 2021 Low-Rank Registration Based Manifolds for Convection-Dominated PDEs AAAI 2021 Machine learning structure preserving brackets for forecasting irreversible processes NeurIPS 2021 Matrix factorisation and the interpretation of geodesic distance NeurIPS 2021 Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent AISTATS 2021 Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions JMLR 2021 Momentum Improves Optimization on Riemannian Manifolds AISTATS 2021 Multidimensional Scaling: Approximation and Complexity ICML 2021