Engineering topics
Publications and source records attributed to Reddy, Tyler [LANL].
This is a Python code base that takes openly-available genetic information on known viruses and performs supervised machine learning and feature importance analysis on the relationship of the viral genomes to the competence to infect humans or bind to a specific host cell receptor.
The code is a set of Python libraries/scripts that leverage open source computer vision packages like YOLO and SAM2 to identify emulsion droplets in plate reader images and videos of microfluidic device flows.
This is a Python library that provides infrastructure for users to train gradient-free (neural network) machine learning models in a variety of problem domains. The avoidance of gradients/backpropagation is achieved by the randomization and fixing of a subset of neural network weights and biases during training.