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Found 6 papers, 3 papers with code
Multi-fidelity Hierarchical Neural Processes
MF-HNP is flexible enough to handle non-nested high dimensional data at different fidelity levels with varying input and output dimensions.
A Deep Learning Based Automatic Defect Analysis Framework for In-situ TEM Ion Irradiations
The system provides analysis of features observed in TEM including both static and dynamic properties using the YOLO-based defect detection module coupled to a geometry analysis module and a dynamic tracking module.
Multi defect detection and analysis of electron microscopy images with deep learning
Electron microscopy is widely used to explore defects in crystal structures, but human detecting of defects is often time-consuming, error-prone, and unreliable, and is not scalable to large numbers of images or real-time analysis.
Deep Bayesian Active Learning for Accelerating Stochastic Simulation
The results demonstrate that STNP outperforms the baselines in the offline learning setting and LIG achieves the state-of-the-art for Bayesian active learning.
Quantifying Uncertainty in Deep Spatiotemporal Forecasting
Deep learning is gaining increasing popularity for spatiotemporal forecasting.
DeepGLEAM: A hybrid mechanistic and deep learning model for COVID-19 forecasting
We introduce DeepGLEAM, a hybrid model for COVID-19 forecasting.
