davidslac Goto Github PK

accyag

Apply transfer learning with vgg net to accelerator yag screens

adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

dlib

A toolkit for making real world machine learning and data analysis applications in C++

gbrop

guided back prop work against psana-mlearn and h5-minibatch

h5-mlearn-minibatch

package to prepare minibatches from h5 input for a machine learning framework.

h5writer

Demo parallel hdf5 writting with psana

keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano or TensorFlow.

labelmeannotationtool

Source code for the LabelMe annotation tool.

mlearntut

Machine learning tutorial

psana-mlearn

Machine learning package, meant for use at LCLS/SLAC, with psana

pylabelme

Simple Image Annotation Tool

ram

"Recurrent Models of Visual Attention" in TensorFlow

regress_xtcav

investigate regression, plots, etc, with xtcav

relevance-prop

investigating relevant propogation

self-seeding

looking at the self seeding data

splitter

sslearningpipeline

vae

trying out vae in keras

vgg_xtcav

Try transfer learning from vgg onto xtcav

xtcav-mlearn

applying machine learning to xtcav analysis. xtcav is a imaging diagnostic for the LCLS beam at SLAC.

xtcav-mlearn-doc

notebook documentation on xtcav machine learning project

yaml-cpp

A YAML parser and emitter in C++