juliusberner / oberwolfach_workshop
Material for 'Mathematics of Deep Learning Workshop' (Invited Talk)
☆17Updated last year
Alternatives and similar repositories for oberwolfach_workshop:
Users that are interested in oberwolfach_workshop are comparing it to the libraries listed below
- Differentiable interface to FEniCS for JAX☆52Updated 3 years ago
- PyTorch implementation of GMLS-Nets. Machine learning methods for scattered unstructured data sets. Methods for learning differential op…☆25Updated last year
- ☆20Updated 3 months ago
- Convolutional Solvers for Partial Differential Equations☆28Updated 4 years ago
- Python library for solving Stochastic Ordinary Differential Equations (SODEs)☆15Updated 12 years ago
- Code for the paper "Variational Monte Carlo Approach to Partial Differential Equations with Neural Networks" (https://arxiv.org/abs/2206.…☆9Updated 2 years ago
- A software package for flexible HPC GPs☆15Updated 2 weeks ago
- Code for the paper "Rational neural networks", NeurIPS 2020☆28Updated 4 years ago
- DifferentialEquations.jl with PyTorch☆11Updated 2 years ago
- ☆15Updated 6 months ago
- Simulation-Enabled Prediction, Inference, and Analysis: physics-informed statistical learning.☆33Updated last year
- Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton☆25Updated 2 years ago
- Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.☆20Updated last year
- Turning SymPy expressions into JAX functions☆43Updated 3 years ago
- Deep renormalized Mori-Zwanzig (DrMZ) Julia package.☆14Updated last year
- Tensor decomposition with arbitrary expressions: inner, outer, elementwise operators; nonlinear transformations; and more.☆58Updated 2 years ago
- Sparse Identification of Truncation Errors (SITE) for Data-Driven Discovery of Modified Differential Equations☆10Updated 5 years ago
- The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …☆14Updated 2 years ago
- Fast extremal eigensolvers for PyTorch.☆17Updated 3 years ago
- Efficient Differentiable n-d PDE solvers in JAX.☆24Updated 3 months ago
- From the paper "Dynamic mode decomposition for multiscale nonlinear physics" by Dylewsky, Tao, & Kutz☆10Updated 4 years ago
- ☆30Updated 2 years ago
- A 30-minute showcase on the how and the why of neural differential equations.☆13Updated 10 months ago
- SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance☆19Updated this week
- Source code for Deep Multigrid method https://arxiv.org/pdf/1711.03825.pdf☆18Updated 5 years ago
- ☆36Updated 3 years ago
- Slides/notes and Jupyter notebook demos for an introductory course of numerical methods for PDEs☆19Updated 9 months ago
- Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation☆12Updated 3 years ago
- ☆21Updated 4 years ago