fwcore / mean-field-theory-deep-learningLinks
paper lists and information on mean-field theory of deep learning
☆78Updated 6 years ago
Alternatives and similar repositories for mean-field-theory-deep-learning
Users that are interested in mean-field-theory-deep-learning are comparing it to the libraries listed below
Sorting:
- Convolutional Neural Tangent Kernel☆113Updated 5 years ago
- NTK reading group☆87Updated 5 years ago
- Repository containing Pytorch code for EKFAC and K-FAC perconditioners.☆146Updated 2 years ago
- ☆67Updated 6 years ago
- Collection of algorithms for approximating Fisher Information Matrix for Natural Gradient (and second order method in general)☆140Updated 6 years ago
- Code for experiments in my blog post on the Neural Tangent Kernel: https://eigentales.com/NTK☆176Updated 5 years ago
- Code for the paper: "Tensor Programs II: Neural Tangent Kernel for Any Architecture"☆105Updated 4 years ago
- ☆170Updated last year
- Hessian spectral density estimation in TF and Jax☆123Updated 4 years ago
- Pytorch implementation of KFAC and E-KFAC (Natural Gradient).☆132Updated 6 years ago
- Hypergradient descent☆149Updated last year
- hessian in pytorch☆187Updated 4 years ago
- Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"☆72Updated 9 years ago
- ☆124Updated last year
- ☆36Updated 4 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆147Updated last year
- Limitations of the Empirical Fisher Approximation☆47Updated 5 months ago
- Monotone operator equilibrium networks☆53Updated 5 years ago
- {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch☆215Updated 2 months ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- pyhessian is a TensorFlow module which can be used to estimate Hessian matrices☆24Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Optimization with orthogonal constraints and on general manifolds☆131Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Code for NeurIPS 2019 paper: "Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes…☆245Updated 4 years ago
- This repository is no longer maintained. Check☆81Updated 5 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 7 years ago
- a python implementation of various versions of the information bottleneck, including automated parameter searching☆128Updated 5 years ago
- ☆54Updated last year