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Found 11 papers, 5 papers with code
TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones
In comparison with the observed tracks, we demonstrate that TROPHY can capture TC characteristics that are comparable to and sometimes even better than a well-validated TC tracking algorithm that requires multiple dynamic and thermodynamic scalar fields.
Neural Stream Functions
Our approach takes a vector field as input and trains an implicit neural representation to learn a stream function for that vector field.
Adaptively Placed Multi-Grid Scene Representation Networks for Large-Scale Data Visualization
We address this shortcoming with an adaptively placed multi-grid SRN (APMGSRN) and propose a domain decomposition training and inference technique for accelerated parallel training on multi-GPU systems.
Multilevel Robustness for 2D Vector Field Feature Tracking, Selection, and Comparison
However, in practice, the computation of classic robustness may produce artifacts when a critical point is close to the boundary of the domain; thus, we do not have a complete picture of the vector field behavior within its local neighborhood.
VDL-Surrogate: A View-Dependent Latent-based Model for Parameter Space Exploration of Ensemble Simulations
In the model inference stage, we predict the latent representations at previously selected viewpoints and decode the latent representations to data space.
GNN-Surrogate: A Hierarchical and Adaptive Graph Neural Network for Parameter Space Exploration of Unstructured-Mesh Ocean Simulations
Our approach improves the efficiency of parameter space exploration with a surrogate model that predicts the simulation outputs accurately and efficiently.
Reinforcement Learning for Load-balanced Parallel Particle Tracing
Second, we propose a workload estimation model, helping RL agents estimate the workload distribution of processes in future computations.
Deep Hierarchical Super Resolution for Scientific Data
We present a novel technique for hierarchical super resolution (SR) with neural networks (NNs), which upscales volumetric data represented with an octree data structure to a high-resolution uniform grid with minimal seam artifacts on octree node boundaries.
InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations
We propose InSituNet, a deep learning based surrogate model to support parameter space exploration for ensemble simulations that are visualized in situ.
Grand Challenge of 106-Point Facial Landmark Localization
However, previous competitions on facial landmark localization (i. e., the 300-W, 300-VW and Menpo challenges) aim to predict 68-point landmarks, which are incompetent to depict the structure of facial components.
Z-checker: A Framework for Assessing Lossy Compression of Scientific Data
However, lossy compressor developers and users are missing a tool to explore the features of scientific datasets and understand the data alteration after compression in a systematic and reliable way.
Other Computer Science Instrumentation and Methods for Astrophysics Computational Engineering, Finance, and Science
