juliusberner / deep_kolmogorov
Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)
☆22Updated 2 years ago
Alternatives and similar repositories for deep_kolmogorov:
Users that are interested in deep_kolmogorov are comparing it to the libraries listed below
- ☆20Updated 3 months ago
- ☆30Updated 2 years ago
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆49Updated last year
- Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics☆49Updated 2 years ago
- Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…☆69Updated 8 months ago
- Refining continuous-in-depth neural networks☆39Updated 3 years ago
- PyTorch implementation of GMLS-Nets. Machine learning methods for scattered unstructured data sets. Methods for learning differential op…☆25Updated last year
- ☆71Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆43Updated 6 years ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆52Updated 3 years ago
- Material for 'Mathematics of Deep Learning Workshop' (Invited Talk)☆17Updated last year
- Solving Inverse Physics Problems with Score Matching☆22Updated last year
- 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
- Neat Bayesian machine learning examples☆54Updated last week
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆35Updated 2 years ago
- Symplectic Recurrent Neural Networks☆27Updated 2 years ago
- A basic implementation of the paper Eigengame : PCA as a Nash Equilibrium☆21Updated 3 years ago
- ☆10Updated 2 years ago
- Simple, extensible implementations of some meta-learning algorithms in Jax☆9Updated 4 years ago
- Models and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"☆16Updated 4 years ago
- Probabilistic Solution of Differential Equations☆13Updated 2 years ago
- Pytorch code for Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC☆12Updated 3 years ago
- ☆11Updated 3 years ago
- Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982☆21Updated 4 years ago
- ☆34Updated 3 years ago
- A pyTorch Extension for Applied Mathematics☆39Updated 4 years ago
- Model hub for all your DiffeqML needs. Pretrained weights, modules, and basic inference infrastructure☆24Updated last year
- Graph Learning with JAX☆14Updated 2 years ago
- ☆14Updated 5 months ago
- Source code for the ICLR'22 paper on "Half-Inverse Gradients"☆18Updated 2 years ago