A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.
A Python-embedded modeling language for convex optimization problems.
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
Assertions, equality checks and other test helpers
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.
Write desktop and web apps in pure Python
Foundry is a blazing fast, portable and modular toolkit for Ethereum application development written in Rust.
Framework for Easily Invertible Architectures
python toolbox for visualizing geographical data and making maps
A highly efficient and modular implementation of Gaussian Processes in PyTorch
:mag: End-to-end Python framework for building natural language search interfaces to data. Leverages Transformers and the State-of-the-Art of NLP. Supports DPR, Elasticsearch, Hugging Face’s Hub, and much more!
Code for the paper "Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification" (2020)
code for KalmanNet
The Official PyTorch Implementation of "LSGM: Score-based Generative Modeling in Latent Space" (NeurIPS 2021)
Simple matlab2python converter
MEND: Fast Model Editing at Scale
Common utilities for ONNX converters
Quant Research Papers
POT : Python Optimal Transport
Companion package of the review paper entitled 'High-dimensional Gaussian sampling: A review and a unifying approach based on a stochastic proximal point algorithm' by Maxime Vono et al.
Synthetic Data Generation for tabular, relational and time series data.
SiliconCompiler is an open source compiler framework that automates translation from source code to silicon.
Statsmodels: statistical modeling and econometrics in Python
UniswapV2 clone made in educational purposes