Andrew Y. Ng

Publication Activity (10 Years)

Years Active: 1995-2024
Publications (10 Years): 103

Top Venues

CoRR

npj Digit. Medicine

MIDL

ML4H@NeurIPS

Publications

Tanvi Deshpande, Eva Prakash, Elsie Gyang Ross, Curtis P. Langlotz, Andrew Y. Ng, Jeya Maria Jose Valanarasu
Auto-Generating Weak Labels for Real & Synthetic Data to Improve Label-Scarce Medical Image Segmentation. CoRR (2024)
Chih-Ying Liu, Jeya Maria Jose Valanarasu, Camila Gonzalez, Curtis P. Langlotz, Andrew Y. Ng, Sergios Gatidis
Unlocking Robust Segmentation Across All Age Groups via Continual Learning. CoRR (2024)
Yixing Jiang, Jeremy Irvin, Ji Hun Wang, Muhammad Ahmed Chaudhry, Jonathan H. Chen, Andrew Y. Ng
Many-Shot In-Context Learning in Multimodal Foundation Models. CoRR (2024)
Yuntao Ma, Hiva Ghanbari, Tianyuan Huang, Jeremy Irvin, Oliver Brady, Sofian Zalouk, Hao Sheng, Andrew Y. Ng, Ram Rajagopal, Mayur Narsude
A System for Automated Vehicle Damage Localization and Severity Estimation Using Deep Learning. IEEE Trans. Intell. Transp. Syst. 25 (6) (2024)
Muhammad Ahmed Chaudhry, Lyna Kim, Jeremy Irvin, Yuzu Ido, Sonia Chu, Jared Thomas Isobe, Andrew Y. Ng, Duncan Watson-Parris
CloudTracks: A Dataset for Localizing Ship Tracks in Satellite Images of Clouds. CoRR (2024)
Feiyang Yu, Mark Endo, Rayan Krishnan, Ian Pan, Andy Tsai, Eduardo Pontes Reis, Eduardo Kaiser Ururahy Nunes Fonseca, Henrique Min Ho Lee, Zahra Shakeri Hossein Abad, Andrew Y. Ng, Curtis P. Langlotz, Vasantha Kumar Venugopal, Pranav Rajpurkar
Evaluating progress in automatic chest X-ray radiology report generation. Patterns 4 (9) (2023)
David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Sasha Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer T. Chayes, Yoshua Bengio
Tackling Climate Change with Machine Learning. ACM Comput. Surv. 55 (2) (2023)
Maya Srikanth, Jeremy Irvin, Brian Wesley Hill, Felipe Godoy, Ishan Sabane, Andrew Y. Ng
An Empirical Study of Automated Mislabel Detection in Real World Vision Datasets. CoRR (2023)
Vivek Shankar, Xiaoli Yang, Vrishab Krishna, Brent Tan, Oscar Silva, Rebecca Rojansky, Andrew Y. Ng, Fabiola Valvert, Edward Briercheck, David Weinstock, Yasodha Natkunam, Sebastian Fernandez-Pol, Pranav Rajpurkar
LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype. CoRR (2023)
Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi
DataPerf: Benchmarks for Data-Centric AI Development. NeurIPS (2023)
Ji Hun Wang, Jeremy Irvin, Beri Kohen Behar, Ha Tran, Raghav Samavedam, Quentin Hsu, Andrew Y. Ng
Weakly-semi-supervised object detection in remotely sensed imagery. CoRR (2023)
Tianyuan Huang, Timothy Dai, Zhecheng Wang, Hesu Yoon, Hao Sheng, Andrew Y. Ng, Ram Rajagopal, Jackelyn Hwang
Detecting Neighborhood Gentrification at Scale via Street-level Visual Data. CoRR (2023)
Cara Van Uden, Jeremy Irvin, Mars Huang, Nathan Dean, Jason Carr, Andrew Y. Ng, Curtis P. Langlotz
How to Train Your CheXDragon: Training Chest X-Ray Models for Transfer to Novel Tasks and Healthcare Systems. CoRR (2023)
Jeremy Irvin, Lucas Tao, Joanne Zhou, Yuntao Ma, Langston Nashold, Benjamin Liu, Andrew Y. Ng
USat: A Unified Self-Supervised Encoder for Multi-Sensor Satellite Imagery. CoRR (2023)
Vivek Shankar, Xiaoli Yang, Vrishab Krishna, Brent Tan, Oscar Silva, Rebecca Rojansky, Andrew Y. Ng, Fabiola Valvert, Edward Briercheck, David Weinstock, Yasodha Natkunam, Sebastian Fernandez-Pol, Pranav Rajpurkar
LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype. ML4H@NeurIPS (2023)
Pratham N. Soni, Siyu Shi, Pranav R. Sriram, Andrew Y. Ng, Pranav Rajpurkar
Contrastive learning of heart and lung sounds for label-efficient diagnosis. Patterns 3 (1) (2022)
Adriel Saporta, Xiaotong Gui, Ashwin Agrawal, Anuj Pareek, Steven Q. H. Truong, Chanh D. T. Nguyen, Van Doan Ngo, Jayne Seekins, Francis G. Blankenberg, Andrew Y. Ng, Matthew P. Lungren, Pranav Rajpurkar
Benchmarking saliency methods for chest X-ray interpretation. Nat. Mac. Intell. 4 (10) (2022)
Yi-Lin Tsai, Jeremy Irvin, Suhas Chundi, João Estacio Gaspar Araujo, Andrew Y. Ng, Christopher B. Field, Peter K. Kitanidis
Improving debris flow evacuation alerts in Taiwan using machine learning. CoRR (2022)
Jon Braatz, Pranav Rajpurkar, Stephanie Zhang, Andrew Y. Ng, Jeanne Shen
Deep Learning-Based Sparse Whole-Slide Image Analysis for the Diagnosis of Gastric Intestinal Metaplasia. CoRR (2022)
Tianyuan Huang, Timothy Dai, Zhecheng Wang, Hesu Yoon, Hao Sheng, Andrew Y. Ng, Ram Rajagopal, Jackelyn Hwang
Detecting Neighborhood Gentrification at Scale via Street-level Visual Data. Big Data (2022)
Damir Vrabac, Akshay Smit, Yujie He, Andrew Y. Ng, Andrew L. Beam, Pranav Rajpurkar
MedSelect: Selective Labeling for Medical Image Classification Using Meta-Learning. MIDL (2022)
Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi
DataPerf: Benchmarks for Data-Centric AI Development. CoRR (2022)
Bryan Zhu, Nicholas Lui, Jeremy Irvin, Jimmy Le, Sahil Tadwalkar, Chenghao Wang, Zutao Ouyang, Frankie Y. Liu, Andrew Y. Ng, Robert B. Jackson
METER-ML: A Multi-Sensor Earth Observation Benchmark for Automated Methane Source Mapping. CDCEO@IJCAI (2022)
Bryan Zhu, Nicholas Lui, Jeremy Irvin, Jimmy Le, Sahil Tadwalkar, Chenghao Wang, Zutao Ouyang, Frankie Y. Liu, Andrew Y. Ng, Robert B. Jackson
METER-ML: A Multi-sensor Earth Observation Benchmark for Automated Methane Source Mapping. CoRR (2022)
Boyang Tom Jin, Raj Palleti, Siyu Shi, Andrew Y. Ng, James V. Quinn, Pranav Rajpurkar, David Kim
Transfer learning enables prediction of myocardial injury from continuous single-lead electrocardiography. J. Am. Medical Informatics Assoc. 29 (11) (2022)
Alexander Ke, William Ellsworth, Oishi Banerjee, Andrew Y. Ng, Pranav Rajpurkar
CheXtransfer: performance and parameter efficiency of ImageNet models for chest X-Ray interpretation. CHIL (2021)
Yen Nhi Truong Vu, Richard Wang, Niranjan Balachandar, Can Liu, Andrew Y. Ng, Pranav Rajpurkar
MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation. MLHC (2021)
Bryan Gopal, Ryan W. Han, Gautham Raghupathi, Andrew Y. Ng, Geoffrey H. Tison, Pranav Rajpurkar
3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations. CoRR (2021)
Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven Q. H. Truong, Du Nguyen Duong, Tan Bui, Pierre Chambon, Yuhao Zhang, Matthew P. Lungren, Andrew Y. Ng, Curtis P. Langlotz, Pranav Rajpurkar
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports. CoRR (2021)
Saahil Jain, Akshay Smit, Steven Q. H. Truong, Chanh D. T. Nguyen, Minh-Thanh Huynh, Mudit Jain, Victoria A. Young, Andrew Y. Ng, Matthew P. Lungren, Pranav Rajpurkar
VisualCheXbert: Addressing the Discrepancy Between Radiology Report Labels and Image Labels. CoRR (2021)
Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren
CheXternal: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays and External Clinical Settings. CoRR (2021)
Bryan Gopal, Ryan W. Han, Gautham Raghupathi, Andrew Y. Ng, Geoffrey H. Tison, Pranav Rajpurkar
3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations. ML4H@NeurIPS (2021)
Soham Uday Gadgil, Mark Endo, Emily Wen, Andrew Y. Ng, Pranav Rajpurkar
CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation. MIDL (2021)
Alexander Ke, William Ellsworth, Oishi Banerjee, Andrew Y. Ng, Pranav Rajpurkar
CheXtransfer: Performance and Parameter Efficiency of ImageNet Models for Chest X-Ray Interpretation. CoRR (2021)
Siyu Shi, Ishaan Malhi, Kevin Tran, Andrew Y. Ng, Pranav Rajpurkar
CheXseen: Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays. CoRR (2021)
Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng, Pranav Rajpurkar
MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. MIDL (2021)
Sharon Zhou, Jiequan Zhang, Hang Jiang, Torbjörn Lundh, Andrew Y. Ng
Data augmentation with Mobius transformations. Mach. Learn. Sci. Technol. 2 (2) (2021)
Akshay Smit, Damir Vrabac, Yujie He, Andrew Y. Ng, Andrew L. Beam, Pranav Rajpurkar
MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning. CoRR (2021)
Mark Endo, Rayan Krishnan, Viswesh Krishna, Andrew Y. Ng, Pranav Rajpurkar
Retrieval-Based Chest X-Ray Report Generation Using a Pre-trained Contrastive Language-Image Model. ML4H@NeurIPS (2021)
Siyu Shi, Ishaan Malhi, Kevin Tran, Andrew Y. Ng, Pranav Rajpurkar
Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays. MIDL (2021)
Soham Gadgil, Mark Endo, Emily Wen, Andrew Y. Ng, Pranav Rajpurkar
CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation. CoRR (2021)
Cécile Logé, Emily Ross, David Yaw Amoah Dadey, Saahil Jain, Adriel Saporta, Andrew Y. Ng, Pranav Rajpurkar
Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management. CoRR (2021)
Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven Q. H. Truong, Du Nguyen Duong, Tan Bui, Pierre Chambon, Yuhao Zhang, Matthew P. Lungren, Andrew Y. Ng, Curtis P. Langlotz, Pranav Rajpurkar
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports. NeurIPS Datasets and Benchmarks (2021)
Emma Chen, Andy Kim, Rayan Krishnan, Jin Long, Andrew Y. Ng, Pranav Rajpurkar
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays. MLHC (2021)
Viswesh Krishna, Anirudh Joshi, Damir Vrabac, Philip L. Bulterys, Eric Yang, Sebastian Fernandez-Pol, Andrew Y. Ng, Pranav Rajpurkar
GloFlow: Whole Slide Image Stitching from Video Using Optical Flow and Global Image Alignment. MICCAI (8) (2021)
Cécile Logé, Emily Ross, David Yaw Amoah Dadey, Saahil Jain, Adriel Saporta, Andrew Y. Ng, Pranav Rajpurkar
Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management. NeurIPS Datasets and Benchmarks (2021)
Yen Nhi Truong Vu, Richard Wang, Niranjan Balachandar, Can Liu, Andrew Y. Ng, Pranav Rajpurkar
MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation. CoRR (2021)
Tianyuan Huang, Zhecheng Wang, Hao Sheng, Andrew Y. Ng, Ram Rajagopal
Learning Neighborhood Representation from Multi-Modal Multi-Graph: Image, Text, Mobility Graph and Beyond. CoRR (2021)
David Eng, Chris Chute, Nishith Khandwala, Pranav Rajpurkar, Jin Long, Sam Shleifer, Mohamed H. Khalaf, Alexander T. Sandhu, Fátima Rodriguez, David J. Maron, Saeed Seyyedi, Daniele Marin, Ilana Golub, Matthew J. Budoff, Felipe Kitamura, Marcelo Straus Takahashi, Ross W. Filice, Rajesh Shah, John Mongan, Kimberly Kallianos, Curtis P. Langlotz, Matthew P. Lungren, Andrew Y. Ng, Bhavik N. Patel
Automated coronary calcium scoring using deep learning with multicenter external validation. npj Digit. Medicine 4 (2021)
Saahil Jain, Akshay Smit, Andrew Y. Ng, Pranav Rajpurkar
Effect of Radiology Report Labeler Quality on Deep Learning Models for Chest X-Ray Interpretation. CoRR (2021)
Emma Chen, Andy Kim, Rayan Krishnan, Jin Long, Andrew Y. Ng, Pranav Rajpurkar
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays. CoRR (2021)
Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Gunnar E. Carlsson, Stefano Ermon
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology. ICLR (2021)
Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren
CheXternal: generalization of deep learning models for chest X-ray interpretation to photos of chest X-rays and external clinical settings. CHIL (2021)
Saahil Jain, Akshay Smit, Steven Q. H. Truong, Chanh D. T. Nguyen, Minh-Thanh Huynh, Mudit Jain, Victoria A. Young, Andrew Y. Ng, Matthew P. Lungren, Pranav Rajpurkar
VisualCheXbert: addressing the discrepancy between radiology report labels and image labels. CHIL (2021)
Nick A. Phillips, Pranav Rajpurkar, Mark Sabini, Rayan Krishnan, Sharon Zhou, Anuj Pareek, Nguyet Minh Phu, Chris Wang, Andrew Y. Ng, Matthew P. Lungren
CheXphoto: 10, 000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. CoRR (2020)
Shih-Cheng Huang, Tanay Kothari, Imon Banerjee, Chris Chute, Robyn L. Ball, Norah Borus, Andrew Huang, Bhavik N. Patel, Pranav Rajpurkar, Jeremy Irvin, Jared Dunnmon, Joseph Bledsoe, Katie S. Shpanskaya, Abhay Dhaliwal, Roham Zamanian, Andrew Y. Ng, Matthew P. Lungren
PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. npj Digit. Medicine 3 (2020)
Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng, Pranav Rajpurkar
MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. CoRR (2020)
Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Phil Chen, Amirhossein Kiani, Jeremy Irvin, Andrew Y. Ng, Matthew P. Lungren
CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting. CoRR (2020)
Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Stefano Ermon
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology. CoRR (2020)
Eric Zelikman, Sharon Zhou, Jeremy Irvin, Cooper Raterink, Hao Sheng, Jack Kelly, Ram Rajagopal, Andrew Y. Ng, David Gagne
Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models. CoRR (2020)
Sharon Zhou, Jiequan Zhang, Hang Jiang, Torbjörn Lundh, Andrew Y. Ng
Data augmentation with Möbius transformations. CoRR (2020)
Jeremy Irvin, Hao Sheng, Neel Ramachandran, Sonja Johnson-Yu, Sharon Zhou, Kyle Story, Rose Rustowicz, Cooper Elsworth, Kemen Austin, Andrew Y. Ng
ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery. CoRR (2020)
Viswesh Krishna, Anirudh Joshi, Philip L. Bulterys, Eric Yang, Andrew Y. Ng, Pranav Rajpurkar
GloFlow: Global Image Alignment for Creation of Whole Slide Images for Pathology from Video. CoRR (2020)
Akshay Smit, Saahil Jain, Pranav Rajpurkar, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren
Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. EMNLP (1) (2020)
Akshay Smit, Saahil Jain, Pranav Rajpurkar, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren
CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. CoRR (2020)
Nick A. Phillips, Pranav Rajpurkar, Mark Sabini, Rayan Krishnan, Sharon Zhou, Anuj Pareek, Nguyet Minh Phu, Chris Wang, Mudit Jain, Du Nguyen Duong, Steven Q. H. Truong, Andrew Y. Ng, Matthew P. Lungren
CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. ML4H@NeurIPS (2020)
Shih-Cheng Huang, Tanay Kothari, Imon Banerjee, Chris Chute, Robyn L. Ball, Norah Borus, Andrew Huang, Bhavik N. Patel, Pranav Rajpurkar, Jeremy Irvin, Jared Dunnmon, Joseph Bledsoe, Katie S. Shpanskaya, Abhay Dhaliwal, Roham Zamanian, Andrew Y. Ng, Matthew P. Lungren
Author Correction: PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. npj Digit. Medicine 3 (2020)
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
OGNet: Towards a Global Oil and Gas Infrastructure Database using Deep Learning on Remotely Sensed Imagery. CoRR (2020)
Damir Vrabac, Akshay Smit, Rebecca Rojansky, Yasodha Natkunam, Ranjana H. Advani, Andrew Y. Ng, Sebastian Fernandez-Pol, Pranav Rajpurkar
DLBCL-Morph: Morphological features computed using deep learning for an annotated digital DLBCL image set. CoRR (2020)
Tony Duan, Avati Anand, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler
NGBoost: Natural Gradient Boosting for Probabilistic Prediction. ICML (2020)
Pranav Rajpurkar, Chloe O'connell, Amit Schechter, Nishit Asnani, Jason Li, Amirhossein Kiani, Robyn L. Ball, Marc Mendelson, Gary Maartens, Daniël J. van Hoving, Rulan Griesel, Andrew Y. Ng, Tom H. Boyles, Matthew P. Lungren
CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV. npj Digit. Medicine 3 (2020)
Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng
Effective Data Fusion with Generalized Vegetation Index: Evidence from Land Cover Segmentation in Agriculture. CVPR Workshops (2020)
Mang Tik Chiu, Xingqian Xu, Kai Wang, Jennifer A. Hobbs, Naira Hovakimyan, Thomas S. Huang, Honghui Shi, Yunchao Wei, Zilong Huang, Alexander G. Schwing, Robert Brunner, Ivan Dozier, Wyatt Dozier, Karen Ghandilyan, David Wilson, Hyunseong Park, Jun Hee Kim, Sungho Kim, Qinghui Liu, Michael C. Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg, Alexandre Barbosa, Rodrigo G. Trevisan, Bingchen Zhao, Shaozuo Yu, Siwei Yang, Yin Wang, Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng, Van Thong Huynh, Soo-Hyung Kim, In Seop Na, Ujjwal Baid, Shubham Innani, Prasad Dutande, Bhakti Baheti, Sanjay N. Talbar, Jianyu Tang
The 1st Agriculture-Vision Challenge: Methods and Results. CVPR Workshops (2020)
Amirhossein Kiani, Bora Uyumazturk, Pranav Rajpurkar, Alex Wang, Rebecca Gao, Erik Jones, Yifan Yu, Curtis P. Langlotz, Robyn L. Ball, Thomas J. Montine, Brock A. Martin, Gerald J. Berry, Michael G. Ozawa, Florette K. Hazard, Ryanne A. Brown, Simon B. Chen, Mona Wood, Libby S. Allard, Lourdes Ylagan, Andrew Y. Ng, Jeanne Shen
Impact of a deep learning assistant on the histopathologic classification of liver cancer. npj Digit. Medicine 3 (2020)
Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Jeremy Irvin, Andrew Y. Ng, Matthew P. Lungren
CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays. CoRR (2020)
Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng
Effective Data Fusion with Generalized Vegetation Index: Evidence from Land Cover Segmentation in Agriculture. CoRR (2020)
Mang Tik Chiu, Xingqian Xu, Kai Wang, Jennifer A. Hobbs, Naira Hovakimyan, Thomas S. Huang, Honghui Shi, Yunchao Wei, Zilong Huang, Alexander G. Schwing, Robert Brunner, Ivan Dozier, Wyatt Dozier, Karen Ghandilyan, David Wilson, Hyunseong Park, Jun Hee Kim, Sungho Kim, Qinghui Liu, Michael C. Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg, Alexandre Barbosa, Rodrigo G. Trevisan, Bingchen Zhao, Shaozuo Yu, Siwei Yang, Yin Wang, Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng, Van Thong Huynh, Soo-Hyung Kim, In Seop Na, Ujjwal Baid, Shubham Innani, Prasad Dutande, Bhakti Baheti, Sanjay N. Talbar, Jianyu Tang
The 1st Agriculture-Vision Challenge: Methods and Results. CoRR (2020)
Tony Duan, Anand Avati, Daisy Yi Ding, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler
NGBoost: Natural Gradient Boosting for Probabilistic Prediction. CoRR (2019)
David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Körding, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer T. Chayes, Yoshua Bengio
Tackling Climate Change with Machine Learning. CoRR (2019)
Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn L. Ball, Katie S. 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
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. AAAI (2019)
Yichen Shen, Maxime Voisin, Alireza Aliamiri, Anand Avati, Awni Y. Hannun, Andrew Y. Ng
Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning. KDD (2019)
Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn L. Ball, Katie S. 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
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. CoRR (2019)
Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng
Countdown Regression: Sharp and Calibrated Survival Predictions. UAI (2019)
Anand Avati, Tony Duan, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng
Countdown Regression: Sharp and Calibrated Survival Predictions. CoRR (2018)
Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah
Improving palliative care with deep learning. BMC Medical Informatics Decis. Mak. 18 (S-4) (2018)
Anand Avati, Stephen Pfohl, Chris Lin, Thao Nguyen, Meng Zhang, Philip Hwang, Jessica Wetstone, Kenneth Jung, Andrew Y. Ng, Nigam H. Shah
Predicting Inpatient Discharge Prioritization With Electronic Health Records. CoRR (2018)
Ziang Xie, Guillaume Genthial, Stanley Xie, Andrew Y. Ng, Dan Jurafsky
Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction. NAACL-HLT (2018)
Andrew L. Maas, Peng Qi, Ziang Xie, Awni Y. Hannun, Christopher T. Lengerich, Daniel Jurafsky, Andrew Y. Ng
Building DNN acoustic models for large vocabulary speech recognition. Comput. Speech Lang. 41 (2017)
Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah
Improving Palliative Care with Deep Learning. CoRR (2017)
Pranav Rajpurkar, Jeremy Irvin, Kaylie Zhu, Brandon Yang, Hershel Mehta, Tony Duan, Daisy Yi Ding, Aarti Bagul, Curtis P. Langlotz, Katie S. Shpanskaya, Matthew P. Lungren, Andrew Y. Ng
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning. CoRR (2017)
Ziang Xie, Sida I. Wang, Jiwei Li, Daniel Lévy, Aiming Nie, Dan Jurafsky, Andrew Y. Ng
Data Noising as Smoothing in Neural Network Language Models. ICLR (Poster) (2017)
Sercan Ömer Arik, Mike Chrzanowski, Adam Coates, Gregory Frederick Diamos, Andrew Gibiansky, Yongguo Kang, Xian Li, John Miller, Andrew Y. Ng, Jonathan Raiman, Shubho Sengupta, Mohammad Shoeybi
Deep Voice: Real-time Neural Text-to-Speech. ICML (2017)
Ziang Xie, Sida I. Wang, Jiwei Li, Daniel Lévy, Aiming Nie, Dan Jurafsky, Andrew Y. Ng
Data Noising as Smoothing in Neural Network Language Models. CoRR (2017)
Sherry Ruan, Jacob O. Wobbrock, Kenny Liou, Andrew Y. Ng, James A. Landay
Comparing Speech and Keyboard Text Entry for Short Messages in Two Languages on Touchscreen Phones. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1 (4) (2017)
Pranav Rajpurkar, Jeremy Irvin, Aarti Bagul, Daisy Yi Ding, Tony Duan, Hershel Mehta, Brandon Yang, Kaylie Zhu, Dillon Laird, Robyn L. Ball, Curtis P. Langlotz, Katie S. Shpanskaya, Matthew P. Lungren, Andrew Y. Ng
MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs. CoRR (2017)
Pranav Rajpurkar, Awni Y. Hannun, Masoumeh Haghpanahi, Codie Bourn, Andrew Y. Ng
Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks. CoRR (2017)
Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah
Improving palliative care with deep learning. BIBM (2017)
Russell Stewart, Mykhaylo Andriluka, Andrew Y. Ng
End-to-End People Detection in Crowded Scenes. CVPR (2016)
Andrew Y. Ng
Deep Learning: What's Next. AAMAS (2016)
Ziang Xie, Anand Avati, Naveen Arivazhagan, Dan Jurafsky, Andrew Y. Ng
Neural Language Correction with Character-Based Attention. CoRR (2016)

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Andrew Y. Ng