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numpy-elm

A Numpy Implementation of Extreme Learning Machine (ELM)

open-solution-home-credit

Open solution to the Home Credit Default Risk challenge :house_with_garden:

paper-list-on-imbalanced-time-series-classification-with-deep-learning

pu-gbdt

Convert the loss function in gbdt to PU-Learning loss function and use the classifier to predict a bank credit dataset

pydl8.5

An algorithm for learning optimal decision trees, with Python interface

pytorch-fm

Factorization Machine models in PyTorch

pytorch-lrp

Basic LRP implementation in PyTorch

pytorchzerotoall

Simple PyTorch Tutorials Zero to ALL!

quantumforest

Fast Differentiable Forest lib with the advantages of both decision trees and neural networks

recurrent-mixture-networks

relative_attributing_propagation

Interpreting DNNs, Relative attributing propagation

rethink-biasvariance-tradeoff

Rethinking Bias-Variance Trade-off for Generalization of Neural Networks

rmi-ai

sda_2019_st_gallen

skmaple

An implementation (sklearn API) of Model Agnostic Supervised Local Explanation (MAPLE) by Plumb et al. and reproduction of "accuracy" experiments.

soft-decision-tree

pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"

spatially-varying-blur-detection-python

python implementation of the paper "Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes" - cvpr 2017

synthetic-financial-datasets-for-fraud-detection

Kaggle - Synthetic datasets generated by the PaySim mobile money simulator

systemic-risk

Some Jupyter notebooks demonstrating various types of models for systemic financial risk, including indicator back-testing, network construction, network analytics, statistical stress-testing & economic models. Many of these can be run on Azure, when the required R & python packages are supported.

systemic_risk

Systemic Risk, ECB Stress Test data

systemic_risk_measures

Comparison of three financial models to measure the system risk of Banks using datasets from Bloomberg.

tabnet

PyTorch implementation of TabNet paper

tabnet-modified

Modification of TabNet as suggested in the Medium article, "The Unreasonable Ineffectiveness of Deep Learning on Tabular Data"

turbulence-and-systemic-risk

Project description: https://medium.com/@tzhangwps/measuring-financial-turbulence-and-systemic-risk-9d9688f6eec1?source=friends_link&sk=15d25da80de749edd1694fc70d0703bb

ugfraud

An Unsupervised Graph-based Toolbox for Fraud Detection

visualizingndf

Official PyTorch implementation of "Visualizing the Decision-making Process in Deep Neural Decision Forest", CVPR 2019 Workshops on Explainable AI

wikienergy

Git repo for Wiki Energy project