Learning to Compose Domain-Specific Transformations for Data Augmentation. - Alexander J. Ratner; Henry R. Ehrenberg; Zeshan Hussain; Jared Dunnmon; Christopher Ré (NIPS, 2017)

Machine Learning for Better Models for Predicting Bond Prices. - Swetava Ganguli; Jared Dunnmon (CoRR, 2017)

Optimizing and Visualizing Deep Learning for Benign/Malignant Classification in Breast Tumors. - Darvin Yi; Rebecca Lynn Sawyer; David Cohn III; Jared Dunnmon; Carson K. Lam; Xuerong Xiao; Daniel L. Rubin (CoRR, 2017)

Snorkel MeTaL: Weak Supervision for Multi-Task Learning. - Alexander Ratner; Braden Hancock; Jared Dunnmon; Roger E. Goldman; Christopher Ré (DEEM@SIGMOD, 2018)

Training Complex Models with Multi-Task Weak Supervision. - Alexander Ratner; Braden Hancock; Jared Dunnmon; Frederic Sala; Shreyash Pandey; Christopher Ré (AAAI, 2019)

Doubly Weak Supervision of Deep Learning Models for Head CT. - Khaled Saab 002; Jared Dunnmon; Roger E. Goldman; Alexander Ratner; Hersh Sagreiya; Christopher Ré; Daniel L. Rubin (MICCAI (3), 2019)

Predicting Food Security Outcomes Using Convolutional Neural Networks (CNNs) for Satellite Tasking. - Swetava Ganguli; Jared Dunnmon; Darren Hau (CoRR, 2019)

Predicting US State-Level Agricultural Sentiment as a Measure of Food Security with Tweets from Farming Communities. - Jared Dunnmon; Swetava Ganguli; Darren Hau; Brooke E. Husic (CoRR, 2019)

Automated abnormality detection in lower extremity radiographs using deep learning. - Maya Varma; Mandy Lu; Rachel Gardner; Jared Dunnmon; Nishith Khandwala; Pranav Rajpurkar; Jin Long; Christopher Beaulieu; Katie S. Shpanskaya; Li Fei-Fei 001; Matthew P. Lungren; Bhavik N. Patel (Nat. Mach. Intell., 2019)

Ivy: Instrumental Variable Synthesis for Causal Inference. - Zhaobin Kuang; Frederic Sala; Nimit Sharad Sohoni; Sen Wu 002; Aldo Córdova-Palomera; Jared Dunnmon; James Priest; Christopher Ré (AISTATS, 2020)

Hidden stratification causes clinically meaningful failures in machine learning for medical imaging. - Luke Oakden-Rayner; Jared Dunnmon; Gustavo Carneiro 001; Christopher Ré (CHIL, 2020)

No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems. - Nimit Sharad Sohoni; Jared Dunnmon; Geoffrey Angus; Albert Gu; Christopher Ré (NeurIPS, 2020)

Assessing Robustness to Noise: Low-Cost Head CT Triage. - Sarah M. Hooper; Jared A. Dunnmon; Matthew P. Lungren; Sanjiv Sam Gambhir; Christopher Ré; Adam S. Wang; Bhavik N. Patel (CoRR, 2020)

Data Valuation for Medical Imaging Using Shapley Value: Application on A Large-scale Chest X-ray Dataset. - Siyi Tang; Amirata Ghorbani; Rikiya Yamashita; Sameer Rehman; Jared A. Dunnmon; James Y. Zou; Daniel L. Rubin (CoRR, 2020)

Let's Hope it Works! Inaccurate Supervision of Neural Networks with Incorrect Labels: Application to Epilepsy. - Florian Dubost; Erin Hong; Daniel Y. Fu; Nandita Bhaskhar; Siyi Tang; Khaled Saab 002; Daniel L. Rubin; Jared Dunnmon; Christopher Lee-Messer (CoRR, 2020)

PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. - Shih-Cheng Huang; Tanay Kothari; Imon Banerjee; Christopher Chute; Robyn L. Ball; Norah Borus; Andrew Huang; Bhavik N. Patel; Pranav Rajpurkar; Jeremy Irvin; Jared Dunnmon; Joseph Bledsoe; et al. (npj Digit. Medicine, 2020)

Author Correction: PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. - Shih-Cheng Huang; Tanay Kothari; Imon Banerjee; Christopher Chute; Robyn L. Ball; Norah Borus; Andrew Huang; Bhavik N. Patel; Pranav Rajpurkar; Jeremy Irvin; Jared Dunnmon; Joseph Bledsoe; et al. (npj Digit. Medicine, 2020)

Weak supervision as an efficient approach for automated seizure detection in electroencephalography. - Khaled Saab 002; Jared Dunnmon; Christopher Ré; Daniel L. Rubin; Christopher Lee-Messer (npj Digit. Medicine, 2020)

Cross-Modal Data Programming Enables Rapid Medical Machine Learning. - Jared A. Dunnmon; Alexander J. Ratner; Khaled Saab 002; Nishith Khandwala; Matthew Markert; Hersh Sagreiya; Roger E. Goldman; Christopher Lee-Messer; Matthew P. Lungren; Daniel L. Rubin; Christopher Ré (Patterns, 2020)

Observational Supervision for Medical Image Classification Using Gaze Data. - Khaled Saab 002; Sarah M. Hooper; Nimit Sharad Sohoni; Jupinder Parmar; Brian Pogatchnik; Sen Wu 002; Jared A. Dunnmon; Hongyang R. Zhang; Daniel L. Rubin; Christopher Ré (MICCAI (2), 2021)

Automated Seizure Detection and Seizure Type Classification From Electroencephalography With a Graph Neural Network and Self-Supervised Pre-Training. - Siyi Tang; Jared A. Dunnmon; Khaled Saab 002; Xuan Zhang; Qianying Huang; Florian Dubost; Daniel L. Rubin; Christopher Lee-Messer (CoRR, 2021)

OncoNet: Weakly Supervised Siamese Network to automate cancer treatment response assessment between longitudinal FDG PET/CT examinations. - Anirudh Joshi; Sabri Eyuboglu; Shih-Cheng Huang; Jared Dunnmon; Arjun Soin; Guido A. Davidzon; Akshay Chaudhari; Matthew P. Lungren (CoRR, 2021)

Comparison of segmentation-free and segmentation-dependent computer-aided diagnosis of breast masses on a public mammography dataset. - Rebecca Sawyer Lee; Jared A. Dunnmon; Ann He; Siyi Tang; Christopher Ré; Daniel L. Rubin (J. Biomed. Informatics, 2021)

ViLMedic: a framework for research at the intersection of vision and language in medical AI. - Jean-Benoit Delbrouck; Khaled Saab 002; Maya Varma; Sabri Eyuboglu; Pierre J. Chambon; Jared Dunnmon; Juan Zambrano; Akshay Chaudhari; Curtis P. Langlotz (ACL (demo), 2022)

Domino: Discovering Systematic Errors with Cross-Modal Embeddings. - Sabri Eyuboglu; Maya Varma; Khaled Kamal Saab; Jean-Benoit Delbrouck; Christopher Lee-Messer; Jared Dunnmon; James Zou 001; Christopher Ré (ICLR, 2022)

Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis. - Siyi Tang; Jared Dunnmon; Khaled Kamal Saab; Xuan Zhang; Qianying Huang; Florian Dubost; Daniel L. Rubin; Christopher Lee-Messer (ICLR, 2022)

xView3-SAR: Detecting Dark Fishing Activity Using Synthetic Aperture Radar Imagery. - Fernando Paolo; Tsu-ting Tim Lin; Ritwik Gupta; Bryce Goodman; Nirav Patel; Daniel Kuster; David Kroodsma; Jared Dunnmon (NeurIPS, 2022)

Multimodal spatiotemporal graph neural networks for improved prediction of 30-day all-cause hospital readmission. - Siyi Tang; Amara Tariq; Jared Dunnmon; Umesh Sharma; Praneetha Elugunti; Daniel L. Rubin; Bhavik N. Patel; Imon Banerjee (CoRR, 2022)

Spatiotemporal Modeling of Multivariate Signals With Graph Neural Networks and Structured State Space Models. - Siyi Tang; Jared A. Dunnmon; Liangqiong Qu; Khaled Kamal Saab; Christopher Lee-Messer; Daniel L. Rubin (CoRR, 2022)

Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models. - Siyi Tang; Jared A. Dunnmon; Liangqiong Qu; Khaled Kamal Saab; Tina Baykaner; Christopher Lee-Messer; Daniel L. Rubin (CHIL, 2023)

Predicting 30-Day All-Cause Hospital Readmission Using Multimodal Spatiotemporal Graph Neural Networks. - Siyi Tang; Amara Tariq; Jared A. Dunnmon; Umesh Sharma; Praneetha Elugunti; Daniel L. Rubin; Bhavik N. Patel; Imon Banerjee (IEEE J. Biomed. Health Informatics, 2023)

Advancing the Scientific Method with Large Language Models: From Hypothesis to Discovery. - Yanbo Zhang; Sumeer Ahmad Khan; Adnan Mahmud; Huck Yang; Alexander Lavin; Michael Levin 001; Jeremy G. Frey; Jared Dunnmon; James A. Evans; Alan R. Bundy; Saso Dzeroski; Jesper Tegnér; et al. (CoRR, 2025)