zzzace2000

nodegam

Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"

dropout-feature-ranking

FIDO-saliency

Explaining Image Classifiers by Counterfactual Generation

mimic-preprocess

MIMIC preprocessing for the ICML paper "Dynamic Measurement Scheduling for Event Forecasting Using Deep RL"

robust_cls_model

The code to reproduce CVPR 2021 paper "Towards Robust Classification Model by Counterfactual and Invariant Data Generation"

GAMs

Multiple Generalized Additive Models implemented in Python (EBM, XGB, Spline, FLAM). Code for our KDD 2021 paper "How Interpretable and Trustworthy are GAMs?" https://arxiv.org/abs/2006.06466

autodiagnosis

Dynamic Measurement Scheduling for Event Forecasting using Deep RL (ICML 2019)

GAMs_models

Multiple Generalized Additive Models implemented in Python (EBM, XGB, Spline, FLAM).

cairl_nodegam

Code for the paper "Extracting Clinician's Goals by What-if Interpretable Modeling"

generative_inpainting

Generative Image Inpainting with Contextual Attention https://arxiv.org/abs/1801.07892, demo http://jiahuiyu.com/deepfill

us_scraper

A simpe scraper to probe the availabiliteis for US visa interviews in Canada

node

Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data

sepsis3-mimic

Evaluation of the Sepsis-3 guidelines in MIMIC-III

EB1A

EB1A Full Application - I-140 and I-485

interpret

Fit interpretable models. Explain blackbox machine learning.

mimic3-benchmarks

Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database.

mywebsite

zzzace2000.github.io