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Found 6 papers, 2 papers with code
Evaluation of Data Augmentation and Loss Functions in Semantic Image Segmentation for Drilling Tool Wear Detection
Furthermore, models are trained on image tiles of different sizes, and augmentation techniques of varying intensities are deployed.
Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind In Situ Data
Additionally, it produced reasonable results on datasets with fewer features and smaller training sets from Wind, STEREO-A and STEREO-B with True Skill Statistics of 0. 56, 0. 57 and 0. 53, respectively.
Vehicle management in a modular production context using Deep Q-Learning
These environments are comprised of a source and sink for the parts to be processed, as well as (several) workstations.
A machine learning pipeline for autonomous numerical analytic continuation of Dyson-Schwinger equations
This has to be done in order to avoid poles and branch cuts in the integrand of the self-energy loop.
Deep reinforcement learning for complex evaluation of one-loop diagrams in quantum field theory
In this paper we present a novel technique based on deep reinforcement learning that allows for numerical analytic continuation of integrals that are often encountered in one-loop diagrams in quantum field theory.
nEoS: Neutron Star Equation of State from hadron physics alone
We contribute a publicly available set of tables and code to provide Equations of State (EoS) for matter at neutron star densities.
General Relativity and Quantum Cosmology High Energy Astrophysical Phenomena High Energy Physics - Phenomenology Nuclear Theory
