Invenia Technical Computing Corporation

The electrical grid is one of the most complex systems ever created

We use machine learning to improve the operational planning of electricity production and distribution, improving reliability, efficiency, transparency, and reducing pollution

We find great purpose in our ability to change the world for the better It's what drives us to work hard and continuously improve If our vision resonates with you and you are interested in joining us, please visit our career page at www joininvenia com to apply

At Invenia we want to support the community by open sourcing various projects we work on

Below is a list of various projects that are open to the world! Here's a blog post on how to contribute to open source too! A Julia interface for Amazon Web Services

The ChainRules package provides a variety of common utilities that can be used by downstream automatic differentiation (AD) tools to define and execute forward-, reverse-, and mixed-mode primitives

The ChainRulesCore package provides a light-weight dependency for defining sensitivities for functions in your packages, without you needing to depend on ChainRules itself

ExprTools provides tooling for working with Julia expressions during metaprogramming This package aims to provide light-weight performant tooling without requiring additional package dependencies

FeatureTransforms jl provides utilities for performing feature engineering in machine learning pipelines with support for AbstractArrays and Tables

Define intervals with left and round bounds

LibPQ jl is a Julia wrapper for the PostgreSQL libpq C library

Allows Julia function calls to be temporarily overloaded for the purpose of testing

NamedDimsArray is a zero-cost abstraction to add names to the dimensions of an array

Invenia's researchers work on numerous interesting topics

This occurs both within the company, and with collaborators beyond

In the spirit of open scholarship, below we have some papers for you to explore!