Jeremy Irvin

TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data

Jeremy Andrew Irvin, Emily Ruoyu Liu, Joyce Chuyi Chen, Ines Dormoy, Jinyoung Kim, Samar Khanna, Zhuo Zheng, Stefano Ermon

Many-Shot In-Context Learning in Multimodal Foundation Models

Yixing Jiang^‡, Jeremy Irvin^‡, Ji Hun Wang, Muhammad Ahmed Chaudhry, Jonathan H Chen, Andrew Y Ng

Deep learning for detecting and characterizing oil and gas well pads in satellite imagery

Neel Ramachandran^‡, Jeremy Irvin^‡, Mark Omara, Ritesh Gautam, Kelsey Meisenhelder, Erfan Rostami, Hao Sheng, Andrew Y Ng, Robert B Jackson

Nature Communications 2024

Automatic deforestation driver attribution using deep learning on satellite imagery

Neel Ramachandran^‡, Jeremy Irvin^‡, Hao Sheng, Sonja Johnson-Yu, Kyle Story, Rose Rustowicz, Andrew Y Ng, Kemen Austin

Global Environmental Change 2024

Geo-bench: Toward foundation models for earth monitoring

Alexandre Lacoste, Nils Lehmann, Pau Rodriguez, Evan Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vazquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu

NeurIPS 2023 Datasets and Benchmarks Track

CloudTracks: A Dataset for Localizing Ship Tracks in Satellite Images of Clouds

Muhammad Ahmed Chaudhry^‡, Lyna Kim^‡, Jeremy Irvin^‡, Yuzu Ido, Sonia Chu, Jared Thomas Isobe, Andrew Y Ng, Duncan Watson-Parris

USat: A Unified Self-Supervised Encoder for Multi-Sensor Satellite Imagery

Jeremy Irvin^‡, Lucas Tao^‡, Joanne Zhou, Yuntao Ma, Langston Nashold, Benjamin Liu, Andrew Y. Ng

An Empirical Study of Automated Mislabel Detection in Real World Vision Datasets

Maya Srikanth^‡, Jeremy Irvin^‡, Brian Wesley Hill, Felipe Godoy, Ishan Sabane, Andrew Y Ng

Weakly-semi-supervised object detection in remotely sensed imagery

Ji Hun Wang^‡, Jeremy Irvin^‡, Beri Kohen Behar, Ha Tran, Raghav Samavedam, Quentin Hsu, Andrew Y. Ng

Tackling Climate Change with Machine Learning at NeurIPS 2023

METER-ML: A Multi-sensor Earth Observation Benchmark for Automated Methane Source Mapping

Bryan Zhu^‡, Nicholas Lui^‡, Jeremy Irvin^‡, Sahil Tadwalkar, Chenghao Wang, Zutao Ouyang, Frankie Y. Liu, Andrew Y. Ng, Robert B. Jackson

IJCAI-ECAI 2022 Workshop on Complex Data Challenges in Earth Observation

Marked crosswalks in US transit-oriented station areas, 2007–2020: A computer vision approach using street view imagery

Meiqing Li^‡, Hao Sheng^‡, Jeremy Irvin^‡, Heejung Chung, Andrew Ying, Tiger Sun, Andrew Y Ng, Daniel A Rodriguez

Environment and Planning B: Urban Analytics and City Science

CheXED: comparison of a deep learning model to a clinical decision support system for pneumonia in the emergency department

Jeremy A Irvin^‡, Anuj Pareek^‡, Jin Long, Pranav Rajpurkar, David Ken-Ming Eng, Nishith Khandwala, Peter J Haug, Al Jephson, Karen E Conner, Benjamin H Gordon, Fernando Rodriguez, Andrew Y Ng, Matthew P Lungren, Nathan C Dean

Journal of Thoracic Imaging

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Jeremy Irvin^‡, Sharon Zhou^‡, Gavin McNicol^‡, Fred Lu, Vincent Liu, Etienne Fluet-Chouinard, Zutao Ouyang, Sara Helen Knox, ..., Andrew Y. Ng, Rob Jackson

Agricultural and Forest Meteorology

OGNet: Towards a Global Oil and Gas Infrastructure Database using Deep Learning on Remotely Sensed Imagery

Hao Sheng^‡, Jeremy Irvin^‡, Sasankh Munukutla, Shawn Zhang, Christopher Cross, Kyle Story, Rose Rustowicz, Cooper Elsworth, Zutao Yang, Mark Omara, Ritesh Gautam, Robert B Jackson, Andrew Y. Ng

Spotlight at NeurIPS 2020 Workshop on Tackling Climate Change with Machine Learning

ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery

Jeremy Irvin^‡, Hao Sheng^‡, Neel Ramachandran, Sonja Johnson-Yu, Sharon Zhou, Kyle Story, Rose Rustowicz, Cooper Elsworth, Kemen Austin^‡‡, Andrew Y Ng^‡‡

NeurIPS 2020 Workshop on Tackling Climate Change with Machine Learning

Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models

Eric Zelikman^‡, Sharon Zhou^‡, Jeremy Irvin^‡, Cooper Raterink, Hao Sheng, Jack Kelly, Ram Rajagopal, Andrew Y Ng^‡‡, David Gagne^‡‡

NeurIPS 2020 Workshop on Tackling Climate Change with Machine Learning

Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression

Pranav Rajpurkar, Jingbo Yang, Nathan Dass, Vinjai Vale, Arielle S. Keller, Jeremy Irvin, Zachary Taylor, Sanjay Basu, Andrew Ng, Leanne M. Williams

JAMA Network Open 2020

Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments

Jeremy Irvin, Andrew A Kondrich, Michael Ko, Pranav Rajpurkar, Behzad Haghgoo, Bruce E Landon, Robert L Phillips, Stephen Petterson, Andrew Y Ng, Sanjay Basu

BMC Public Health 2020

AppendiXNet: Deep Learning for Diagnosis of Appendicitis from A Small Dataset of CT Exams Using Video Pretraining

Pranav Rajpurkar^‡, Allison Park^‡, Jeremy Irvin^‡, Chris Chute, Michael Bereket, Domenico Mastrodicasa, Curtis P. Langlotz, Matthew P. Lungren, Andrew Y. Ng^‡‡, Bhavik N. Patel^‡‡

Nature Scientific Reports 2020

DeepWind: Weakly Supervised Localization of Wind Turbines in Satellite Imagery

Sharon Zhou^‡, Jeremy Irvin^‡, Zhecheng Wang, Eva Zhang, Jabs Aljubran, Will Deadrick, Ram Rajagopal, Andrew Ng

NeurIPS Climate Change Workshop 2019

Human–machine partnership with artificial intelligence for chest radiograph diagnosis

Bhavik N Patel, Louis Rosenberg, Gregg Willcox, David Baltaxe, Mimi Lyons, Jeremy Irvin, Pranav Rajpurkar, Timothy Amrhein, Rajan Gupta, Safwan Halabi, Curtis Langlotz, Edward Lo, Joseph Mammarappallil, AJ Mariano, Geoffrey Riley, Jayne Seekins, Luyao Shen, Evan Zucker, Matthew Lungren

NPJ digital medicine 2019

Real-time electronic interpretation of digital chest images using artificial intelligence in emergency department patients suspected of pneumonia

Nathan Dean, Jeremy A Irvin, Pranav Rajpurkar, Al Jephson, Karen Conner, Mathew P Lungren

European Respiratory Journal 2019

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison

Jeremy Irvin^‡, Pranav Rajpurkar^‡, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn Ball, Katie Shpanskaya, Jayne Seekins, David A Mong, Safwan S Halabi, Jesse K Sandberg, Ricky Jones, David B Larson, Curtis P Langlotz, Bhavik N Patel, Matthew P Lungren^‡‡, Andrew Y Ng^‡‡

Thirty-Third AAAI Conference on Artificial Intelligence 2019

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: development and retrospective validation of MRNet

Nicholas Bien^‡, Pranav Rajpurkar^‡, Robyn L Ball, Jeremy Irvin, Allison Park, Erik Jones, Michael Bereket, Bhavik N Patel, Kristen W Yeom, Katie Shpanskaya, Safwan Halabi, Evan Zucker, Gary Fanton, Derek F Amanatullah, Christopher F Beaulieu, Geoffrey M Riley, Russell J Stewart, Francis G Blankenberg, David B Larson, Ricky H Jones, Curtis P Langlotz, Andrew Y Ng^‡‡, Matthew P Lungren^‡‡

PLoS medicine 2018

Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists

Pranav Rajpurkar^‡, Jeremy Irvin^‡, Robyn L Ball, Kaylie Zhu, Brandon Yang, Hershel Mehta, Tony Duan, Daisy Ding, Aarti Bagul, Curtis P Langlotz, Bhavik N Patel, Kristen W Yeom, Katie Shpanskaya, Francis G Blankenberg, Jayne Seekins, Timothy J Amrhein, David A Mong, Safwan S Halabi, Evan J Zucker, Andrew Y Ng^‡‡, Matthew P Lungren^‡‡

PLoS medicine 2018

MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs

Pranav Rajpurkar^‡, Jeremy Irvin^‡, Aarti Bagul, Daisy Ding, Tony Duan, Hershel Mehta, Brandon Yang, Kaylie Zhu, Dillon Laird, Robyn L Ball, Curtis Langlotz, Katie Shpanskaya, Matthew P Lungren^‡‡, Andrew Y Ng^‡‡

1st Conference on Medical Imaging with Deep Learning 2018

Radiology SWARM: novel crowdsourcing tool for CheXNet algorithm validation

Safwan Halabi, Matthew Lungren, Louis Rosenberg, David Baltaxe, Bhavik Patel, Jayne Seekins, Francis Blakenberg, David Mong, Timothy Amrhein, Pranav Raipurkar, David Larson, Jeremy Irvin, Robyn Ball, Curtis P Langlotz, Gregg Willcox

SiiM Conference on Machine Intelligence in Medical Imaging 2018

Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning

Pranav Rajpurkar^‡, Jeremy Irvin^‡, Kaylie Zhu, Brandon Yang, Hershel Mehta, Tony Duan, Daisy Ding, Aarti Bagul, Curtis Langlotz, Katie Shpanskaya, Matthew P Lungren^‡‡, Andrew Y Ng^‡‡

arXiv preprint 2017

Explicit Causal Connections between the Acquisition of Linguistic Tiers: Evidence from Dynamical Systems Modeling

Daniel Spokoyny, Jeremy Irvin, Fermin Moscoso del Prado Martin

Proceedings of the 7th Workshop on Cognitive Aspects of Computational Language Learning 2016

Dynamical systems modeling of the child-mother dyad: Causality between child-directed language complexity and language development.

Jeremy Irvin, Daniel Spokoyny, Fermin Moscoso del Prado Martin

CogSci 2016