A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
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Apr 18, 2025 - Python
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A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
Encoding physics to learn reaction-diffusion processes
3D CNN to predict single-phase flow velocity fields
[Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled Training; Rollout Metrics)
A framework based on the tensor train decomposition for working with multivariate functions and multidimensional arrays
Multi-fidelity Generative Deep Learning Turbulent Flows
Dimension reduced surrogate construction for parametric PDE maps
In this repository I publish the python code, that was part of my master thesis. The thesis can be found here, however its in German though, sry. :/
Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs
Python package 'dgpsi' for deep and linked Gaussian process emulations
Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions
[ESWA] NeuroXAI: Adaptive, Robust, Explainable Surrogate Framework for Determination of Channel Importance in EEG Application
Physics-Informed Neural Network, Finite Element Method enhanced neural network, and FEM data-based neural network
PyTorch implemention of the Position-induced Transformer for operator learning in partial differential equations
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning
A GNN-based surrogate model of urban drainage networks.
A toolbox for the calibration and evaluation of simulation models.
A python package for surrogate models that interface with calibration and other tools
Evaluating model calibration methods for sensitivity analysis, uncertainty analysis, optimisation, and Bayesian inference
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