Pinned Repositories
deep_kolmogorov
Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning
deeperwin
DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electron Schrödinger equation. DeepErwin supports weight-sharing when optimizing wave functions for multiple nuclear geometries and the usage of pre-trained neural network weights to accelerate optimization.
EffDI
Python package to compute the effective dispersion index (EffDI).
HARNet
TensorFlow implementation of the HARNet model for realized volatility forecasting.
robust_kolmogorov
Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning (ICML 2022)
theory2practice
Training ReLU networks to high uniform accuracy is intractable
Mathematics of Data Science / University of Vienna's Repositories
mdsunivie/deeperwin
DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electron Schrödinger equation. DeepErwin supports weight-sharing when optimizing wave functions for multiple nuclear geometries and the usage of pre-trained neural network weights to accelerate optimization.
mdsunivie/HARNet
TensorFlow implementation of the HARNet model for realized volatility forecasting.
mdsunivie/deep_kolmogorov
Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning
mdsunivie/theory2practice
Training ReLU networks to high uniform accuracy is intractable
mdsunivie/EffDI
Python package to compute the effective dispersion index (EffDI).
mdsunivie/robust_kolmogorov
Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning (ICML 2022)