kazukiosawa / ngd_in_wide_nnLinks
simple JAX-/NumPy-based implementations of NGD with exact/approximate Fisher Information Matrix both in parameter-space and function-space (by empirical/analytical NTK).
☆14Updated 4 years ago
Alternatives and similar repositories for ngd_in_wide_nn
Users that are interested in ngd_in_wide_nn are comparing it to the libraries listed below
Sorting:
- ☆80Updated 3 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆20Updated 3 years ago
- [NeurIPS'19] Deep Equilibrium Models Jax Implementation☆40Updated 4 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Course Website☆9Updated 3 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- Bayesian algorithm execution (BAX)☆50Updated 3 years ago
- Normalizing Flows using JAX☆84Updated last year
- ☆169Updated last year
- Monotone operator equilibrium networks☆53Updated 5 years ago
- ☆52Updated 2 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Models and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"☆16Updated 5 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Adaptive gradient descent without descent☆48Updated 3 years ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆56Updated 4 years ago
- Probabilistic Solution of Differential Equations☆13Updated 3 years ago
- Bayesian inference with Python and Jax.☆34Updated 2 years ago
- [ICLR 2022] Path integral sampler☆50Updated last year
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 2 years ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆56Updated 4 years ago
- Official code for UnICORNN (ICML 2021)☆27Updated 3 years ago
- Code for Understanding and Mitigating Exploding Inverses in Invertible Neural Networks (AISTATS 2021) http://arxiv.org/abs/2006.09347☆30Updated 4 years ago
- Riemannian Optimization Using JAX☆51Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 5 months ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Nonparametric Differential Equation Modeling☆54Updated last year
- Bayesian Optimization with Density-Ratio Estimation☆24Updated 2 years ago