Mauro Silberberg's starred repositories
EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
DifferentialEquations.jl
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
sharingbuttons.io
Quickly generate social sharing buttons with a tiny performance footprint
python-ternary
:small_red_triangle: Ternary plotting library for python with matplotlib
colour-demosaicing
CFA (Colour Filter Array) demosaicing algorithms for Python
awesome-causality
Resources related to causality
numba-progress
A progress bar implementation in numba using tqdm.
biosimulations
A platform for sharing and reusing biomodeling studies including models, simulations, and visualizations of their results
napari-time-slicer
A meta plugin for processing timelapse data timepoint by timepoint in napari