nrkarthikeyan / topology-decision-boundariesLinks
Topology of decision boundaries
☆28Updated 5 years ago
Alternatives and similar repositories for topology-decision-boundaries
Users that are interested in topology-decision-boundaries are comparing it to the libraries listed below
Sorting:
- Deprecated repository for "Deep Learning with Topological Signatures"☆36Updated 5 years ago
- Open source Python library for topological data analysis (TDA)☆79Updated 8 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆56Updated 6 years ago
- Code for the paper 'Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology'☆31Updated 6 years ago
- Notebooks for IPAM Tutorial, March 15 2019☆24Updated 6 years ago
- MATLAB implementation of linear support vector classification in hyperbolic space☆20Updated 7 years ago
- ☆21Updated 2 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- This code accompanies the paper "Persistence Images: A Stable Vector Representation of Persistent Homology".☆43Updated 4 years ago
- My persistent homology related code.☆26Updated 5 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.☆74Updated 9 years ago
- Pytorch package for geometric softmax☆12Updated 6 years ago
- Python implementation of smooth optimal transport.☆60Updated 4 years ago
- Courses and practical sessions for the Optimal Transport and Machine learning course at Statlearn 2018☆26Updated 7 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Practical sessions for the Optimal Transport and Machine learning course at DS3 2018☆91Updated 7 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 7 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Python library for working with kernel methods in machine learning☆121Updated 6 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆183Updated 7 years ago
- Dirichlet Process K-means☆48Updated last year
- Python implementation of Robust Continuous Clustering☆106Updated 6 years ago
- Implementation of the Sliced Wasserstein Autoencoders☆90Updated 7 years ago
- Code for "Efficient optimization of loops and limits with randomized telescoping sums"☆27Updated 6 years ago
- Learning and Reasoning with Graph-Structured Data (ICML 2019 Workshop)☆26Updated 6 years ago
- Code for the paper "A Kernel Test of Goodness of Fit" by Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton☆25Updated 9 years ago
- Wasserstein regularization for sparse multi-task regression☆15Updated 5 years ago
- Topological Data Analysis in Python: Simplicial Complex☆123Updated 2 weeks ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆105Updated 5 years ago