fmeirinhos / pytorch-hessianfree
PyTorch implementation of Hessian Free optimisation
☆43Updated 5 years ago
Alternatives and similar repositories for pytorch-hessianfree:
Users that are interested in pytorch-hessianfree are comparing it to the libraries listed below
- Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.☆74Updated 7 months ago
- Pytorch implementation of KFAC and E-KFAC (Natural Gradient).☆130Updated 5 years ago
- Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations☆20Updated last year
- Limitations of the Empirical Fisher Approximation☆47Updated 2 weeks ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆145Updated last year
- ☆67Updated 6 years ago
- Monotone operator equilibrium networks☆51Updated 4 years ago
- paper lists and information on mean-field theory of deep learning☆75Updated 5 years ago
- Hessian spectral density estimation in TF and Jax☆122Updated 4 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆86Updated 2 years ago
- Adaptive gradient descent without descent☆47Updated 3 years ago
- Repository containing Pytorch code for EKFAC and K-FAC perconditioners.☆141Updated last year
- The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"☆25Updated 5 years ago
- Lipschitz Neural Networks described in "Sorting Out Lipschitz Function Approximation" (ICML 2019).☆55Updated 4 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆48Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Convex potential flows☆83Updated 3 years ago
- ☆157Updated 2 years ago
- ☆47Updated 5 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆49Updated 4 years ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆54Updated 4 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- ☆83Updated 5 years ago
- Experiments with Neural ODEs and Adversarial Attacks☆44Updated 6 years ago
- hessian in pytorch☆187Updated 4 years ago
- Efficient Riemannian Optimization on Stiefel Manifold via Cayley Transform☆38Updated 5 years ago
- Convolutional Neural Tangent Kernel☆109Updated 5 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- ☆53Updated 7 months ago
- Code release for the ICLR paper☆20Updated 6 years ago