5 papers
ENTIRE: Learning-based Volume Rendering Time Prediction
Zikai Yin, Hamid Gadirov, Jiri Kosinka +1
We introduce ENTIRE, a novel deep learning-based approach for fast and accurate volume rendering time prediction. Predicting rendering time is inherently challenging due to its dep…
SENSE: Self-Supervised Neural Embeddings for Spatial Ensembles
Hamid Gadirov, Lennard Manuel, Steffen Frey
Analyzing and visualizing scientific ensemble datasets with high dimensionality and complexity poses significant challenges. Dimensionality reduction techniques and autoencoders ar…
TRACE: Reconstruction-Based Anomaly Detection in Ensemble and Time-Dependent Simulations
Hamid Gadirov, Martijn Westra, Steffen Frey
Detecting anomalies in high-dimensional, time-dependent simulation data is challenging due to complex spatial and temporal dynamics. We study reconstruction-based anomaly detection…
HyperFLINT: Hypernetwork-based Flow Estimation and Temporal Interpolation for Scientific Ensemble Visualization
Hamid Gadirov, Qi Wu, David Bauer +3
We present HyperFLINT (Hypernetwork-based FLow estimation and temporal INTerpolation), a novel deep learning-based approach for estimating flow fields, temporally interpolating sca…
FLINT: Learning-based Flow Estimation and Temporal Interpolation for Scientific Ensemble Visualization
Hamid Gadirov, Jos B. T. M. Roerdink, Steffen Frey
We present FLINT (learning-based FLow estimation and temporal INTerpolation), a novel deep learning-based approach to estimate flow fields for 2D+time and 3D+time scientific ensemb…