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David Dao

Login: daviddao

Company: @DS3Lab ETH Zurich

Location: Zurich, CH

Bio: cogito ergo sum( ); //!

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Repositories

3mk-script: A script in tex for the KIT lecture "multilingual human computer interaction"
attentive-siamese-cnn: Siamese CNN with STN to learn replicate feature maps
awesome-very-deep-learning: A curated list of papers and code about very deep neural networks
awful-ai: Awful AI is a curated list to track current scary usages of AI - hoping to raise awareness
BBBC021_cropped_data: Cropped cell dataset from BBBC021, sorted after compound treatment and concentration, DNA stain only, Filename is ObjectKey
bbbc_utils: Utility scripts for loading BBBC datasets
biojs-ebi: BioJS workshop page
biojs-io-newick: Newick Parser in JS - parses newick strings into JSON and JSON into newick
biojs-rest-ensembl: REST API for the ensembl website
biojs-vis-tsne: Easy to use t-SNE Visualisation for the web
biojs-workshopper: an automated workshopper build for easier following workshop instructions in biojs [under construction]
biovis-webservice: A web service framework visualizing biological data sets
CellProfiler: CellProfiler is open-source cellular image analysis software.
CellProfiler-Analyst: Software for exploring and analyzing large, high-dimensional image-derived data.
CellProfiler-REST: A REST API for CellProfiler Classifier
conv-vae: Convolutional Variational Autoencoder for EC2 GPU instance test
CPA-docs: Manual for CellProfiler Analyst 2.2 WIP
cpa-multiclass: first draft of a fresh cpa
cyto: null
data: data from experiments
ddm-script: Notes for Distributed Data Mining Lab Course at TUM
debug-macros: A collection of useful debug macros for C
deep-autonomous-driving-papers: A curated list of papers of deep learning in autonomous driving papers :oncoming_automobile:
deepdream: null
deep-learning-book: MIT Deep Learning Book in PDF format
deep-learning-notes: deep learning for the visually impaired
Deep-Learning-Papers-Reading-Roadmap: Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
deep-learning-slides: Deep Learning in Action is an event organized by @munichacm - Materials :movie_camera: :blue_book:!
deep-residual-networks: Deep Residual Learning for Image Recognition
dmc: 1. Place Data Mining Cup src for the TUM Lecture "Business Analytics".
drawingConvNets: A sample application with three different CNN activator functions
ebi-d3-layouts: A short introductory talk about D3s layout idea
ebi-exercise: Hands-ons for the EBI Industry Workshop about BioJS
ebi-exercise-solution: Solutions for the EBI exercise
eccb-workshop-biojs-d3: These are my stack.js slides for the ECCB 14 Workshop in Strasbourg. Please have a look at the index.html !
essential-c: A C data structure library for rapid prototyping
exelixis: Interactive and easy-to-use phylogenetic tree viewer for the web
functional-programming-scala: Assignments of the Coursera class by Martin Odersky
functional-vis-example: example
genesis: A framework for working with genetic data.
Ghost: Just a blogging platform
github-markdown-toc: Easy TOC creation for GitHub README.md
GPU-Programming-TUM: This is a repository for the GPU Programming Lab Course at TUM
imitation: Contains an implementation of "Trust Region Policy Optimization" (TRPO)
intro-to-gp-notebooks: Gaussian process (GP) introductory ipython notebooks by Yakir Reshef
ladder: Ladder network is a deep learning algorithm that combines supervised and unsupervised learning.
lego-mindstorms-praktikum: null
luminosity: CellProfiler Luminosity
LxMLS-labs-solution: My solutions for the Machine Learning Summer School in Lisbon 2015
metabolism: null
minimal-biojs: null
models: Models built with TensorFlow
module-skeleton: bare bones introduction to modules
msa-tree: A modular combination of MSA viewer and phylogenetic tree viewer
muts-needle-plot: A needle plot for mutation data
neon: Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana?
ngraph: Beautiful Graphs
node-ar-drone: A node.js client for controlling Parrot AR Drone 2.0 quad-copters.
nodelegend: nodelegend for ngraph.pixel
notes: :notebook: My personal notebook where I collect useful links and readings for all kinds of topics
nvidia-deep-learning-tutorial: IPython Notebooks from the NVIDIA tutorial at Harvard ComputeFest (Torch, Caffe, Theano)
oek: null
omniglot: Omniglot data set for one-shot learning
polymerase: polymerase website draft
prediction-market-tutorial: How to build your own predictive market
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers: aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
python-guide: Python best practices guidebook, written for Humans.
pytorch-neural-search-optimizer: PyTorch implementation of Neural Optimizer Search's Optimizer_1
pytorch-without-a-phd: PyTorch version of TensorFlow without a PhD
RF-Opt: Tomas and Davids secret RF Opt
rf-optimizer: Based on RAxML's PlausibilityChecker, the RF-Opt algorithm compares a large phylogeny with a set of small trees and optimizes the average Robinson Fould distance via pruning.
rf-py: Python scripts for extracting and working with bipartitions
rf-py-dev: Private Development Repo
shape-analysis: MATLAB programming solutions for the TUM lecture "Analysis of Three-Dimensional Shapes"
spark-workshop: A Typesafe Activator tutorial for Apache Spark.
spatial-transformer-tensorflow: Tensorflow Implementation of Spatial Transformer Networks
sphinx_rtd_theme: Sphinx theme for readthedocs.org
study-scripts: My personal learning scripts
subpop-ladder: Ladder neural network for cell subpopulation classification
subtree-generator: Creates a huge number of unrooted subtrees from a large phylogeny
teatalk: teatalk landing page
tensorflow: Computation using data flow graphs for scalable machine learning
tensorflow-mnist-tutorial: Sample code for "Tensorflow and deep learning, without a PhD" presentation and code lab.
tensorflow_tutorials: From the basics to slightly more interesting applications of Tensorflow
tflearn: Deep learning library featuring a higher-level API for TensorFlow.
three.js: JavaScript 3D library.
tsne-algorithm: This is a fork of the tSNEJS library for npm
TUM_GPUComputerVision: TUM - (IN2106, IN4102) - Advanced Practical Course - GPU Programming in Computer Vision WS2013/14
vagrant-cpa: Vagrant environment for CellProfiler Analyst and CellProfiler
vega-datasets: Common repository for example datasets used by Vega-related projects
visualise-newick: small website to visualise newick formats
vizbi-recap: Presentation Slides for the BioJS VIZBI workshop
x-bio-pv: null
x-drawrnajs: null
x-muts-needle-plot: null
YAP_TAZ_cluster_data: data generator for splitting dataset for CPA to extract the image tiles

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This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.