OptMLGroup / SQN
Sampled Quasi-Newton Methods for Deep Learning
☆21Updated 4 years ago
Alternatives and similar repositories for SQN:
Users that are interested in SQN are comparing it to the libraries listed below
- Implementation of SVRG and SAGA optimization algorithms for deep learning topics.☆72Updated 4 years ago
- Experiments with Neural ODEs and Adversarial Attacks☆44Updated 6 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆47Updated 6 years ago
- ☆46Updated 7 years ago
- Random Fourier Features☆50Updated 7 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 4 years ago
- The Deep Weight Prior, ICLR 2019☆44Updated 3 years ago
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- ☆26Updated 6 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- This is the code associated with the paper A Variational Inequality Perspective for Generative Adversarial Networks.☆39Updated 5 years ago
- PyTorch implementation of Hessian Free optimisation☆43Updated 5 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆60Updated 6 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated last month
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations☆20Updated 2 years ago
- ☆66Updated 6 years ago
- Models and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"☆16Updated 4 years ago
- The code for Meta Learning for SGMCMC☆25Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 9 months ago
- The code for the paper: https://arxiv.org/abs/1806.06317☆24Updated 5 years ago
- Stochastic Mirror Descent on CIFAR-10☆19Updated 5 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆21Updated 6 years ago
- ☆28Updated 5 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"☆25Updated 5 years ago