gknilsen / pyhessianLinks
pyhessian is a TensorFlow module which can be used to estimate Hessian matrices
☆24Updated 4 years ago
Alternatives and similar repositories for pyhessian
Users that are interested in pyhessian are comparing it to the libraries listed below
Sorting:
- Minimax Optimization, Stackelberg Games, Generative Adversarial Networks☆19Updated 5 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 3 months ago
- Geometric Certifications of Neural Nets☆42Updated 2 years ago
- Collection of algorithms for approximating Fisher Information Matrix for Natural Gradient (and second order method in general)☆139Updated 6 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- paper lists and information on mean-field theory of deep learning☆78Updated 6 years ago
- Hypergradient descent☆148Updated last year
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- ☆26Updated 6 years ago
- NTK reading group☆87Updated 5 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Randomized Smoothing of All Shapes and Sizes (ICML 2020).☆52Updated 4 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"☆25Updated 5 years ago
- This repository contains a simple implementation of Interval Bound Propagation (IBP) using TensorFlow: https://arxiv.org/abs/1810.12715☆160Updated 5 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆21Updated 6 years ago
- The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size☆17Updated 6 years ago
- A Pytorch implementation of the KWNG estimator☆14Updated 11 months ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- This repository contains the Julia code for the paper "Competitive Gradient Descent"☆25Updated 5 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated 2 years ago
- ☆133Updated 7 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- PyTorch implementation of FIM and empirical FIM☆61Updated 6 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 5 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 5 years ago
- Monotone operator equilibrium networks☆52Updated 5 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 6 years ago
- Convolutional Neural Tangent Kernel☆111Updated 5 years ago