ndexter / MLFALinks
Machine Learning Function Approximation: This code implements the fully-connected Deep Neural Network (DNN) architectures considered in the paper "The gap between theory and practice in function approximation with deep neural networks" available at https://arxiv.org/abs/2001.07523
☆18Updated 4 years ago
Alternatives and similar repositories for MLFA
Users that are interested in MLFA are comparing it to the libraries listed below
Sorting:
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- Prototypes of differentiable differential equation solvers in JAX.☆27Updated 5 years ago
- Monotone operator equilibrium networks☆53Updated 5 years ago
- A differentiation API for PyTorch☆30Updated 5 years ago
- ☆22Updated 5 years ago
- ☆80Updated 3 years ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆56Updated 4 years ago
- Discontinuous Hamiltonian Monte Carlo in JAX☆41Updated 5 years ago
- Dive into Jax, Flax, XLA and C++☆31Updated 5 years ago
- [NeurIPS'19] Deep Equilibrium Models Jax Implementation☆40Updated 4 years ago
- "Parameter origami" -- folding and unfolding collections of parameters for optimization and sensitivity analysis.☆14Updated last year
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- A framework for composing Neural Processes in Julia☆76Updated 4 years ago
- Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimatio…☆26Updated 10 years ago
- ☆12Updated 4 years ago
- Computing gradients and Hessians of feed-forward networks with GPU acceleration☆19Updated last year
- Convex potential flows☆83Updated 3 years ago
- ☆51Updated 11 months ago
- Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.☆75Updated 11 months ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆25Updated 7 years ago
- A pytorch version of hamiltonian monte carlo☆14Updated 6 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Repo reproducing experimental results in "Addressing the Topological Defects of Disentanglement"☆22Updated 3 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 5 years ago
- Turning SymPy expressions into JAX functions☆45Updated 4 years ago
- code for "Semi-Discrete Normalizing Flows through Differentiable Tessellation"☆26Updated 2 years ago
- Python 3.6 and TensorFlow implementation of the AReS and MaRS algorithms☆11Updated 6 years ago
- Package for CGD and ACGD optimizers☆20Updated 2 years ago
- ☆102Updated 4 years ago