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Preferential proximal policy optimization in reinforcement learning
(2023-12-01)
The Proximal Policy Optimization (PPO), a policy gradient method, excels in reinforcement learning with its ”surrogate” objective function and stochastic gradient ascent. However, PPO does not fully consider the significance ...
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 ...
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 ...