7 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…
Machine Learning for Scientific Visualization: Ensemble Data Analysis
Hamid Gadirov
Scientific simulations and experimental measurements produce vast amounts of spatio-temporal data, yet extracting meaningful insights remains challenging due to high dimensionality…
GSCache: Real-Time Radiance Caching for Volume Path Tracing using 3D Gaussian Splatting
David Bauer, Qi Wu, Hamid Gadirov +1
Real-time path tracing is rapidly becoming the standard for rendering in entertainment and professional applications. In scientific visualization, volume rendering plays a crucial…
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…