Title
Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation N. Jethani A. Saporta Rajesh Ranganath FAtt 29 10 0 24 Feb 2023
Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers Wanqian Yang Polina Kirichenko Micah Goldblum A. Wilson DRL 27 10 0 28 Nov 2022
Confound-leakage: Confound Removal in Machine Learning Leads to Leakage Sami U Hamdan Bradley C. Love G. V. Polier Susanne Weis H. Schwender Simon B. Eickhoff K. Patil 16 8 0 17 Oct 2022
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics Shoaib Ahmed Siddiqui Nitarshan Rajkumar Tegan Maharaj David M. Krueger Sara Hooker 39 27 0 20 Sep 2022
Deep Learning-Based Automatic Diagnosis System for Developmental Dysplasia of the Hip Yang Li Leo Yan Li-Han H. Tian 24 1 0 07 Sep 2022
Rethinking Machine Learning Model Evaluation in Pathology Syed Ashar Javed Dinkar Juyal Zahil Shanis S. Chakraborty Harsha Pokkalla Aaditya (Adi) Prakash LM&MA 25 12 0 11 Apr 2022
Debiasing pipeline improves deep learning model generalization for X-ray based lung nodule detection M. J. Horry Subrata Chakraborty B. Pradhan M. Paul Jing Zhu H. Loh P. Barua Usha R. Acharya AI4CE 33 7 0 24 Jan 2022
Randomness In Neural Network Training: Characterizing The Impact of Tooling Donglin Zhuang Xingyao Zhang S. Song Sara Hooker 25 75 0 22 Jun 2021
Machine learning-based analysis of hyperspectral images for automated sepsis diagnosis Maximilian Dietrich Silvia Seidlitz Nicholas Schreck Manuel Wiesenfarth Patrick Godau ... Felix Nickel Beat P. Müller-Stich A. Kopp-Schneider Markus A. Weigand Lena Maier-Hein 25 10 0 15 Jun 2021
Disrupting Model Training with Adversarial Shortcuts Ivan Evtimov Ian Covert Aditya Kusupati Tadayoshi Kohno AAML 18 10 0 12 Jun 2021
The Federated Tumor Segmentation (FeTS) Challenge Sarthak Pati Ujjwal Baid M. Zenk Brandon Edwards Micah J. Sheller ... Lena Maier-Hein Jens Kleesiek Bjoern H. Menze Klaus Maier-Hein Spyridon Bakas FedML OOD 41 72 0 12 May 2021
IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography A. Barnett F. Schwartz Chaofan Tao Chaofan Chen Yinhao Ren J. Lo Cynthia Rudin 31 133 0 23 Mar 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 653 0 20 Mar 2021
Teaching with Commentaries Aniruddh Raghu M. Raghu Simon Kornblith D. Duvenaud Geoffrey E. Hinton 12 24 0 05 Nov 2020
Cough Against COVID: Evidence of COVID-19 Signature in Cough Sounds Piyush Bagad Aman Dalmia Jigar Doshi Arsha Nagrani Parag Bhamare A. Mahale S. Rane N. Agarwal R. Panicker 26 112 0 17 Sep 2020
A Survey of Deep Learning for Scientific Discovery M. Raghu Erica Schmidt OOD AI4CE 38 120 0 26 Mar 2020
Making deep neural networks right for the right scientific reasons by interacting with their explanations P. Schramowski Wolfgang Stammer Stefano Teso Anna Brugger Xiaoting Shao Hans-Georg Luigs Anne-Katrin Mahlein Kristian Kersting 23 207 0 15 Jan 2020
Saliency is a Possible Red Herring When Diagnosing Poor Generalization J. Viviano B. Simpson Francis Dutil Yoshua Bengio Joseph Paul Cohen FAtt 15 6 0 01 Oct 2019
Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging Luke Oakden-Rayner Jared A. Dunnmon G. Carneiro Christopher Ré OOD 16 372 0 27 Sep 2019