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Found 5 papers, 1 papers with code
A Self-Supervised Approach to Reconstruction in Sparse X-Ray Computed Tomography
However, obtaining high-quality object reconstructions for the training dataset requires high x-ray dose measurements that can destroy or alter the specimen before imaging is complete.
Hyperparameter Optimization of Generative Adversarial Network Models for High-Energy Physics Simulations
We show that given proper hyperparameter tuning, we can find GANs that provide high-quality approximations of the desired quantities.
HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization
We present a new software, HYPPO, that enables the automatic tuning of hyperparameters of various deep learning (DL) models.
Surrogate Optimization of Deep Neural Networks for Groundwater Predictions
Sustainable management of groundwater resources under changing climatic conditions require an application of reliable and accurate predictions of groundwater levels.
Cosmic Inference: Constraining Parameters With Observations and Highly Limited Number of Simulations
Cosmological probes pose an inverse problem where the measurement result is obtained through observations, and the objective is to infer values of model parameters which characterize the underlying physical system -- our Universe.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics
