fedorajzf

alphafold

Open source code for AlphaFold.

blackbox-backprop

Torch modules that wrap blackbox combinatorial solvers according to the method presented in "Differentiating Blackbox Combinatorial Solvers"

causal-inference-tutorial

Repository with code and slides for a tutorial on causal inference.

cfcausal

R package cfcausal

conformal

Tools for conformal inference in regression

data-driven-pdes

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

DiffGeoOps

This repository contains a Python implementation of the paper "Discrete Differential-Geometry Operators for Triangulated 2-Manifolds" by Meyer et. al. VisMath 2002

dowhy

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.

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.

graph_nets

Build Graph Nets in Tensorflow

IntrinsicallyEfficientStableOPE

kernel_reg

Pytorch implementation of regularization methods for deep networks obtained via kernel methods.

lp-sparsemap

LP-SparseMAP: Differentiable sparse structured prediction in coarse factor graphs

minigo

An open-source implementation of the AlphaGoZero algorithm

models

Models and examples built with TensorFlow

neural-structural-optimization

Neural reparameterization improves structural optimization

oracle_cb

Experimentation for oracle based contextual bandit algorithms.

probml-notebooks

Notebooks for "Probabilistic Machine Learning" book

py-orthpol

Construct orhogonal polynomials using Python

pyprobml

Python code for "Machine learning: a probabilistic perspective" (2nd edition)

ranking

Learning to Rank in TensorFlow

RLSeq2Seq

Deep Reinforcement Learning For Sequence to Sequence Models

Seq2Set

Code for the paper "A Deep Reinforced Sequence-to-Set Model for Multi-Label Classification"

SGM

Sequence Generation Model for Multi-label Classification (COLING 2018)

slides

SurvivalAnalysis

tutorials-2

uncertainty_estimation_deep_learning

This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as described in "A General Framework for Uncertainty Estimation in Deep Learning" (Loquercio, Segù, Scaramuzza. RA-L 2020).

uq-course

Introduction to Uncertainty Quantification