506 citations · 894 across the 7 of their papers we have counts for
8 papers
Unsteady Cylinder Wakes from Arbitrary Bodies with Differentiable Physics-Assisted Neural Network
Shuvayan Brahmachary, Nils Thuerey
This work delineates a hybrid predictive framework configured as a coarse-grained surrogate for reconstructing unsteady fluid flows around multiple cylinders of diverse configurati…
WeatherBench Probability: A benchmark dataset for probabilistic medium-range weather forecasting along with deep learning baseline models
Sagar Garg, Stephan Rasp, Nils Thuerey
WeatherBench is a benchmark dataset for medium-range weather forecasting of geopotential, temperature and precipitation, consisting of preprocessed data, predefined evaluation metr…
Modeling of the nonlinear flame response of a Bunsen-type flame via multi-layer perceptron
Nilam Tathawadekar, Nguyen Anh Khoa Doan, Camilo F. Silva +1
This paper demonstrates the ability of neural networks to reliably learn the nonlinear flame response of a laminar premixed flame, while carrying out only one unsteady CFD simulati…
Learned Turbulence Modelling with Differentiable Fluid Solvers: Physics-based Loss-functions and Optimisation Horizons
Björn List, Li-Wei Chen, Nils Thuerey
In this paper, we train turbulence models based on convolutional neural networks. These learned turbulence models improve under-resolved low resolution solutions to the incompressi…
Numerical investigation of minimum drag profiles in laminar flow using deep learning surrogates
Li-Wei Chen, Berkay Alp Cakal, Xiangyu Hu +1
Efficiently predicting the flowfield and load in aerodynamic shape optimisation remains a highly challenging and relevant task. Deep learning methods have been of particular intere…
Data-driven medium-range weather prediction with a Resnet pretrained on climate simulations: A new model for WeatherBench
Stephan Rasp, Nils Thuerey
Numerical weather prediction has traditionally been based on physical models of the atmosphere. Recently, however, the rise of deep learning has created increased interest in purel…
WeatherBench: A benchmark dataset for data-driven weather forecasting
Stephan Rasp, Peter D. Dueben, Sebastian Scher +3
Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains. A natural question to ask is whether data-driven methods could al…
Volumetric Isosurface Rendering with Deep Learning-Based Super-Resolution
Sebastian Weiss, Mengyu Chu, Nils Thuerey +1
Rendering an accurate image of an isosurface in a volumetric field typically requires large numbers of data samples. Reducing the number of required samples lies at the core of res…