OptMLGroup / SQNLinks
Sampled Quasi-Newton Methods for Deep Learning
☆22Updated 5 years ago
Alternatives and similar repositories for SQN
Users that are interested in SQN are comparing it to the libraries listed below
Sorting:
- PyTorch implementation of Hessian Free optimisation☆43Updated 5 years ago
- Implementation of SVRG and SAGA optimization algorithms for deep learning topics.☆72Updated 4 years ago
- The code for the paper: https://arxiv.org/abs/1806.06317☆24Updated 6 years ago
- Adaptive gradient descent without descent☆48Updated 3 years ago
- Materials for ORIE 7191: Topics in Optimization for Machine Learning☆44Updated 6 years ago
- Random Fourier Features☆50Updated 8 years ago
- Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)☆45Updated 7 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 6 years ago
- Zeroth-order Min-max Optimization☆11Updated 4 years ago
- This is the code associated with the paper A Variational Inequality Perspective for Generative Adversarial Networks.☆40Updated 6 years ago
- Accompanying code for our NeurIPS 2019 paper☆12Updated 5 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 3 months ago
- Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations☆20Updated 2 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 11 months ago
- A suite of stochastic optimization methods for solving the empirical risk minimization problem.☆16Updated 5 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆39Updated 3 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Experiments with Neural ODEs and Adversarial Attacks☆44Updated 6 years ago
- Convolutional Neural Tangent Kernel☆111Updated 5 years ago
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 5 years ago
- Python and MATLAB code for Stein Variational sampling methods☆25Updated 6 years ago
- The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"☆25Updated 5 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Monotone operator equilibrium networks☆52Updated 4 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- Machine Learning Function Approximation: This code implements the fully-connected Deep Neural Network (DNN) architectures considered in t…☆18Updated 4 years ago
- Multi-Information Source Optimization☆23Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago