vikashg / Geometry-Reading-list
A curated list of reading material and lecture notes for all things geometry. Mostly focussed on differential and Riemannian geometry with applications to physics, medical imaging and computer vision.
☆18Updated 7 years ago
Alternatives and similar repositories for Geometry-Reading-list:
Users that are interested in Geometry-Reading-list are comparing it to the libraries listed below
- Examples of more involved applications using Geomstats☆32Updated 4 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Python implementation of the paper "Discrete Differential-Geometry Operators for Triangulated 2-Manifolds" by Meyer et. al. VisMath 2002☆52Updated last year
- Notebooks for IPAM Tutorial, March 15 2019☆24Updated 6 years ago
- We simulate a wind tunnel, place a rectangular occlusion in it, and then use gradient descent to turn the occlusion into a wing.☆25Updated 4 years ago
- Python tools for Morse Smale Complex analysis and visualization☆10Updated 3 years ago
- GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021☆49Updated 2 years ago
- Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"☆42Updated last year
- Automated shapeshifting for function recovery in damaged robots.☆13Updated 4 years ago
- B-Spline CNNs on Lie groups☆53Updated 5 years ago
- Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)☆13Updated 5 years ago
- Official repository for our ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology☆36Updated 4 years ago
- ☆16Updated 6 years ago
- The official implementation of the "Hypernetwork approach to generating point clouds" paper☆26Updated last year
- ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.☆16Updated 7 months ago
- ☆19Updated 3 years ago
- Neural Fixed-Point Acceleration for Convex Optimization☆29Updated 2 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆28Updated last month
- Scale-invariant Learning by Physics Inversion (NeurIPS 2022)☆10Updated 2 years ago
- A differentiation API for PyTorch☆30Updated 4 years ago
- Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561☆24Updated 4 years ago
- Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…☆18Updated 5 years ago
- Optimal Transport for Dummies - Code, slides and article☆32Updated 7 years ago
- Code for Unbiased Implicit Variational Inference (UIVI)☆14Updated 6 years ago
- This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of Coordinate Independent…☆72Updated last year
- Code for "Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations"☆23Updated 2 years ago
- J. Solomon, F. de Goes, G. Peyré, M. Cuturi, A. Butscher, A. Nguyen, T. Du, L. Guibas. Convolutional Wasserstein Distances: Efficient Opt…☆104Updated 7 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- Contact-Aware Symplectic Integrator Network☆12Updated 2 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆55Updated 5 years ago