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On deep learning in physics
(2021-04-01)
Machine learning, and most notably deep neural networks, have seen unprecedented success in recent years due to their ability to learn complex nonlinear mappings by ingesting large amounts of data through the process of ...
Molecular dynamics simulations and neural network solutions for applications in biophysics
(2022-12-01)
As computing resources evolved and became more accessible over time, much of scientific research shifted towards utilizing computational techniques. In particular, biophysics is a field of science that has continually ...
Opportunities for the deep neural network method of solving partial differential equations in the computational study of biomolecules driven through periodic geometries
(2022-08-01)
As deep learning emerged in the 2010s to become a groundbreaking technology in machine vision and natural language processing, it also ushered in many new algorithms for use in scientific research. Among these is the neural ...
DL-based defense against polymorphic network attacks
(2024-01-01)
Network security is of vital importance in our world dominated by internet systems. These systems are vulnerable to large-scale rapidly evolving attacks by sophisticated cyber attackers who can have an upper edge over the ...