Deep Learning
A modular, production-ready framework for training neural networks to detect binary blackhole merge signals in the presence of non-Gaussian background noise, with a focus on efficiency and scale.
Deep Learning
A framework similar to BBHNet for using neural networks to regress from witnessed environmental noise to noise observed in the interferometer strain channel to increase search sensitivity.
hermes Deep Learning
Tools for accelerating, serving, and making streaming asynchronous inference requests to complex ensembles of deep learning models at scale.
ml4gw Deep Learning
Torch utilities for training neural networks for gravitational wave physics applications.
Just For Fun
High level introduction to ML concepts starting from rules-based AI and introducing ML as an extension of it. Working on a follow-up to introduce the concepts of over-fitting and complexity. Good example of how to leverage Github Workflows for publishing.
Deep Learning
Pipeline for training ResNet50 using TensorFlow in a Kaggle notebook, with hypeparameter search performed by cross-validation with HyperBand.
Deep Learning
Now out-of-date project using the Tensorflow Estimator API to asynchronously train multiple MLP workers on sparse data on a single GPU. Planning to update to more modern Keras syntax when I have the time.
Just For Fun
Analyzing airport arrival lead time as a cost-optimization problem, with solutions estimated from suspect TSA data.
Just For Fun
AWS Elastic Beanstalk/RDS application for a DIY fantasy surf league.