f-t-s / CGDLinks
This repository contains the Julia code for the paper "Competitive Gradient Descent"
☆25Updated 6 years ago
Alternatives and similar repositories for CGD
Users that are interested in CGD are comparing it to the libraries listed below
Sorting:
- Monotone operator equilibrium networks☆54Updated 5 years ago
- Limitations of the Empirical Fisher Approximation☆49Updated 9 months ago
- ☆126Updated last year
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- ☆54Updated last year
- Collection of algorithms for approximating Fisher Information Matrix for Natural Gradient (and second order method in general)☆142Updated 6 years ago
- Convolutional Neural Tangent Kernel☆112Updated 6 years ago
- paper lists and information on mean-field theory of deep learning☆78Updated 6 years ago
- ☆172Updated last year
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 5 years ago
- Geometric Certifications of Neural Nets☆42Updated 3 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 6 years ago
- ☆68Updated 6 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆102Updated 7 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- Hessian spectral density estimation in TF and Jax☆124Updated 5 years ago
- Neural Fixed-Point Acceleration for Convex Optimization☆29Updated 3 years ago
- Minimax Optimization, Stackelberg Games, Generative Adversarial Networks☆19Updated 5 years ago
- ☆30Updated 4 years ago
- Adaptive gradient descent without descent☆50Updated 4 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 3 years ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆58Updated 4 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆16Updated 3 years ago
- Code for the paper: "Tensor Programs II: Neural Tangent Kernel for Any Architecture"☆106Updated 5 years ago
- The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) p…☆41Updated 5 years ago
- The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size☆19Updated 6 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆20Updated 6 years ago
- Codebase for Learning Invariances in Neural Networks☆96Updated 3 years ago
- Code for Unbiased Implicit Variational Inference (UIVI)☆15Updated 6 years ago