SIBILA: A novel interpretable ensemble of general-purpose machine learning models applied to medical contexts

12 May 2022

Papers citing "SIBILA: A novel interpretable ensemble of general-purpose machine learning models applied to medical contexts"

11 / 11 papers shown

Title
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Satyapriya Krishna Tessa Han Alex Gu Steven Wu S. Jabbari Himabindu Lakkaraju 241 193 0 03 Feb 2022
Scientific Machine Learning Benchmarks Jeyan Thiyagalingam Mallikarjun Shankar Geoffrey C. Fox Tony (Anthony) John Grenville Hey 47 114 0 25 Oct 2021
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning Yang Liu Sujay Khandagale Colin White Willie Neiswanger 98 66 0 23 Jun 2021
AutoML to Date and Beyond: Challenges and Opportunities Shubhra (Santu) Karmaker Md. Mahadi Hassan Micah J. Smith Lei Xu Chengxiang Zhai K. Veeramachaneni 100 230 0 21 Oct 2020
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch Esteban Real Chen Liang David R. So Quoc V. Le 75 225 0 06 Mar 2020
FLAML: A Fast and Lightweight AutoML Library Chi Wang Qingyun Wu Markus Weimer Erkang Zhu 70 203 0 12 Nov 2019
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations R. Mothilal Amit Sharma Chenhao Tan CML 106 1,020 0 19 May 2019
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 21,864 0 22 May 2017
Deep Learning for Computational Chemistry Garrett B. Goh Nathan Oken Hodas Abhinav Vishnu AI4CE 71 679 0 17 Jan 2017
Deep Learning in Bioinformatics Seonwoo Min Byunghan Lee Sungroh Yoon AI4CE 3DV 60 1,360 0 21 Mar 2016
SMOTE: Synthetic Minority Over-sampling Technique Nitesh Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 361 25,642 0 09 Jun 2011