BaoWangMath / LaplacianSmoothing-GradientDescentLinks
The code for the paper: https://arxiv.org/abs/1806.06317
☆24Updated 6 years ago
Alternatives and similar repositories for LaplacianSmoothing-GradientDescent
Users that are interested in LaplacianSmoothing-GradientDescent are comparing it to the libraries listed below
Sorting:
- Lipschitz Neural Networks described in "Sorting Out Lipschitz Function Approximation" (ICML 2019).☆57Updated 5 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 6 months ago
- The code for the paper: https://arxiv.org/pdf/1802.00168.pdf☆17Updated 5 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 5 years ago
- Implementation of the Sliced Wasserstein Autoencoders☆90Updated 7 years ago
- ☆53Updated 7 years ago
- This repository is no longer maintained. Check☆81Updated 5 years ago
- Geometric Certifications of Neural Nets☆42Updated 2 years ago
- Riemannian approach to batch normalization☆22Updated 7 years ago
- Optimization with orthogonal constraints and on general manifolds☆130Updated 5 years ago
- A pytorch implementation of our jacobian regularizer to encourage learning representations more robust to input perturbations.☆128Updated last year
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆61Updated 7 years ago
- ☆124Updated last year
- Hypergradient descent☆149Updated last year
- ☆60Updated 2 years ago
- Scaled MMD GAN☆36Updated 5 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- This repository contains the code to reproduce the core results from the paper "The Numerics of GANs".☆46Updated 7 years ago
- PyTorch implementation of Hessian Free optimisation☆43Updated 5 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆103Updated 6 years ago
- Notebooks for IPAM Tutorial, March 15 2019☆24Updated 6 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆58Updated 7 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆56Updated 6 years ago
- SGD and Ordered SGD codes for deep learning, SVM, and logistic regression☆35Updated 5 years ago
- Pytorch implementation of 'Semi-Implicit Methods for Deep Neural Networks'☆25Updated 6 years ago
- Implements stochastic line search☆118Updated 2 years ago
- Learning generative models with Sinkhorn Loss☆30Updated 6 years ago
- Nonlinear SVGD for Learning Diversified Mixture Models☆13Updated 6 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 6 years ago
- [AISTATS2020] The official repository of "Invertible Generative Modling using Linear Rational Splines (LRS)".☆20Updated 2 years ago