lie group

Theseus: A Library for Differentiable Nonlinear Optimization NeurIPS 2022 Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces ICML 2022 Auto-Encoding Transformations in Reparameterized Lie Groups for Unsupervised Learning AAAI 2021 Commutative Lie Group VAE for Disentanglement Learning ICML 2021 Equivariant Manifold Flows NeurIPS 2021 GeomNet: A Neural Network Based on Riemannian Geometries of SPD Matrix Space and Cholesky Space for 3D Skeleton-Based Interaction Recognition ICCV 2021 Group Equivariant Conditional Neural Processes ICLR 2021 LieTransformer: Equivariant Self-Attention for Lie Groups ICML 2021 Nonparametric Continuous Sensor Registration JMLR 2021 On Path Integration of Grid Cells: Group Representation and Isotropic Scaling NeurIPS 2021 Tangent Space Backpropagation for 3D Transformation Groups CVPR 2021 B-Spline CNNs on Lie groups ICLR 2020 Disentangling by Subspace Diffusion NeurIPS 2020 Efficient Derivative Computation for Cumulative B-Splines on Lie Groups CVPR 2020 Fast Markov chain Monte Carlo algorithms via Lie groups AISTATS 2020 Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data ICML 2020 Nonparametric Object and Parts Modeling With Lie Group Dynamics CVPR 2020 Stochastic Flows and Geometric Optimization on the Orthogonal Group ICML 2020 Variational Optimization on Lie Groups, with Examples of Leading (Generalized) Eigenvalue Problems AISTATS 2020 Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group ICML 2019 Efficient and Robust Registration on the 3D Special Euclidean Group ICCV 2019 Multi-Frequency Phase Synchronization ICML 2019 Reparameterizing Distributions on Lie Groups AISTATS 2019 A Combinatorial Solution to Non-Rigid 3D Shape-To-Image Matching CVPR 2017 Deep Learning on Lie Groups for Skeleton-Based Action Recognition CVPR 2017