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Geometry

720 directly classified papers

Papers per year

Papers

Reproducing Kernels and New Approaches in Compositional Data Analysis JMLR 2023
On Coresets for Clustering in Small Dimensional Euclidean spaces ICML 2023
SIGMA: Scale-Invariant Global Sparse Shape Matching ICCV 2023
A Unified Analysis of Multi-task Functional Linear Regression Models with Manifold Constraint and Composite Quadratic Penalty JMLR 2023
Limits of Dense Simplicial Complexes JMLR 2023
A Riemannian Exponential Augmented Lagrangian Method for Computing the Projection Robust Wasserstein Distance NIPS 2023
Non-Euclidean Self-Organizing Maps IJCAI 2022
Graph-Coupled Oscillator Networks ICML 2022
Hyperbolic Relevance Matching for Neural Keyphrase Extraction NAACL 2022
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets ICML 2022
Scanline Homographies for Rolling-Shutter Plane Absolute Pose CVPR 2022
Topologically penalized regression on manifolds JMLR 2022
Efficient computation of the the volume of a polytope in high-dimensions using Piecewise Deterministic Markov Processes AISTATS 2022
Mode estimation on matrix manifolds: Convergence and robustness AISTATS 2022
Relative Pose From a Calibrated and an Uncalibrated Smartphone Image CVPR 2022
DeepCurrents: Learning Implicit Representations of Shapes With Boundaries CVPR 2022
Nested Hyperbolic Spaces for Dimensionality Reduction and Hyperbolic NN Design CVPR 2022
Lagrangian manifold Monte Carlo on Monge patches AISTATS 2022
The Flag Median and FlagIRLS CVPR 2022
Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces ICML 2022
Improved Coresets for Euclidean $k$-Means NIPS 2022
Reliable Inlier Evaluation for Unsupervised Point Cloud Registration AAAI 2022
Measure Estimation in the Barycentric Coding Model ICML 2022
Invariance-Aware Randomized Smoothing Certificates NIPS 2022
Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering ICML 2022