HelioWebIntel Corporation
flowchart
I[Intel Corporation]
PI["Parent Institutions (0)"]
CI["Child Institutions (0)"]
AW["Affiliated Works (24)"]
CA["Linked Collaborating Authors (6)"]
I== skos:broader ==>PI
CI== skos:broader ==>I
AW== affil ==>I
AW== author ==>CA
click PI "#parent-institutions"
click CI "#child-institutions"
click AW "#affiliated-works"
click CA "#collaborating-authors"
Parent Institutions [?]
Child Institutions [?]
Affiliated Works
sorted by decreasing year, and then by display-name
- Energetics of Nanocrystalline TiO<SUB>2</SUB>
- Analysis of NO/NO<SUB>2</SUB> Exchange and the Evolution of ClO/ClONO<SUB>2</SUB>/NO<SUB>2</SUB> During SOLVE
- Non-thermal production of molecular oxygen on the surface of Europa
- The Use of Wireless Sensor Networks in Soil Ecology
- Hybrid parallelism for Weather Research and Forecasting Model on Intel platforms
- Scientists as Correspondents: Exploratorium "Ice Stories" for International Polar Year Project Educational Outreach
- Scalable Algorithms for Unsupervised Classification and Anomaly Detection in Large Geospatiotemporal Data Sets
- Evaluating an Explicitly Coupled 3-D Soil Thermal-Hydrology and Carbon Nitrogen Reactive Transport Land Surface Model - CLM-PFLOTRAN
- Scalable Algorithms for Clustering Large Geospatiotemporal Data Sets on Manycore Architectures
- Deep Learning @15 Petaflops/second: Semi-supervised pattern detection for 15 Terabytes of climate data
- EarthInsights: Parallel Clustering of Large Earth Science Datasets on the Summit Supercomputer
- Parallel K-means Clustering of Geospatiotemporal Data Sets Using Manycore CPU Architectures
- Project DisCo: Physics-Based Discovery of Coherent Structures in Spatiotemporal Systems
- Infusing Diversity into Arctic and Antarctic Programs
- Towards Data-Driven Discovery of Extreme Weather Events
- Towards Unsupervised Segmentation of Extreme Weather Events
- Comparison of calcium scaling in thermally driven (MD) and pressure driven (NF) membrane desalination processes
- Classification of Solar Wind Discontinuities Using Supervised Machine Learning
- Classification of Solar Wind Structures via Unsupervised Machine Learning
- Federated causal inference for out-of-distribution generalization in predicting physiological effects of radiation exposure
- Generating informative and accurate descriptions of natural hazards and phenomena using large transformer-based models
- 3D Reconstructions of the Solar Atmosphere using Neural Radiance Fields
- Mapping the Sun and its Irradiance in Extreme Ultraviolet from any Viewpoint with an End-to-End ML Pipeline
- Unsupervised Extreme Weather Segmentation