3 papers
cs.LG2026
A Validated LBM Dataset and Pipeline for Surrogate Modeling of Turbulent 3D Obstructed Channel Flows
Lukas Schröder, Shubham Kavane, Harald Köstler
Evaluating neural operators for 3D turbulent flow requires validated datasets with physical benchmarks. We present a reproducible pipeline generating training data for 3D channel f…
cs.GR2025
ChannelFlow-Tools: A Configuration-Driven Pipeline for Generating Machine-Learning-Ready Datasets of 3D Obstructed Channel Flows
Shubham Kavane, Lukas Schröder, Kajol Kulkarni +2
Data-driven surrogate models are increasingly used in computational fluid dynamics, and their reliability depends on the quality of the training data. These models are typically tr…
cs.LG2023
Dynamically Weighted Federated k-Means
Patrick Holzer, Tania Jacob, Shubham Kavane
Federated clustering, an integral aspect of federated machine learning, enables multiple data sources to collaboratively cluster their data, maintaining decentralization and preser…