gbaydin / hypergradient-descentLinks
Hypergradient descent
☆147Updated last year
Alternatives and similar repositories for hypergradient-descent
Users that are interested in hypergradient-descent are comparing it to the libraries listed below
Sorting:
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 7 years ago
- hessian in pytorch☆187Updated 5 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆102Updated 7 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆61Updated 6 years ago
- Collection of algorithms for approximating Fisher Information Matrix for Natural Gradient (and second order method in general)☆142Updated 6 years ago
- This repository is no longer maintained. Check☆81Updated 5 years ago
- ☆126Updated last year
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- paper lists and information on mean-field theory of deep learning☆79Updated 6 years ago
- Optimization with orthogonal constraints and on general manifolds☆130Updated 5 years ago
- Memory efficient MAML using gradient checkpointing☆86Updated 6 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆148Updated 2 years ago
- Convolutional Neural Tangent Kernel☆112Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 7 years ago
- Repository containing Pytorch code for EKFAC and K-FAC perconditioners.☆152Updated 2 years ago
- ☆135Updated 8 years ago
- Computing various norms/measures on over-parametrized neural networks☆50Updated 7 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 8 years ago
- Codebase for Learning Invariances in Neural Networks☆96Updated 3 years ago
- Implements stochastic line search☆118Updated 2 years ago
- Code for "Recurrent Independent Mechanisms"☆120Updated 3 years ago
- Testing Nerual Tangent Kernel (NTK) on small UCI datasets☆80Updated 6 years ago
- Understanding normalizing flows☆132Updated 6 years ago
- Autoregressive Energy Machines☆78Updated 3 years ago
- NTK reading group☆87Updated 6 years ago
- ☆35Updated 4 years ago
- ☆68Updated 6 years ago
- [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs☆109Updated 5 years ago
- Real NVP PyTorch a Minimal Working Example | Normalizing Flow☆142Updated 5 years ago