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ORCIDAndrew Y. Ng
Andrew Yan-Tak Ng – 吳恩達
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- unicode name: 吳恩達
- affiliation: Stanford University, Computer Science Department
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2020 – today
- 2024
[j36]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): 5627-5639 (2024)- [i66]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 abs/2401.14486 (2024) - [i65]Chih-Ying Liu, Jeya Maria Jose Valanarasu, Camila González, Curtis P. Langlotz, Andrew Y. Ng, Sergios Gatidis:
Unlocking Robust Segmentation Across All Age Groups via Continual Learning. CoRR abs/2404.13185 (2024) - [i64]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 abs/2404.17033 (2024) - [i63]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 abs/2405.09798 (2024) - 2023
- [j35]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): 42:1-42:96 (2023) - [j34]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): 100802 (2023) - [c194]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: 528-558 - [c193]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 - [i62]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 abs/2301.01842 (2023) - [i61]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 abs/2305.08017 (2023) - [i60]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 abs/2311.09574 (2023) - [i59]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 abs/2311.17449 (2023) - [i58]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 abs/2312.02199 (2023) - [i57]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 abs/2312.02200 (2023) - 2022
- [j33]Boyang Tom Jin, Raj Palleti, Siyu Shi, Andrew Y. Ng, James V. Quinn, Pranav Rajpurkar, David A. Kim:
Transfer learning enables prediction of myocardial injury from continuous single-lead electrocardiography. J. Am. Medical Informatics Assoc. 29(11): 1908-1918 (2022) - [j32]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): 867-878 (2022) - [j31]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): 100400 (2022) - [c192]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. IEEE Big Data 2022: 1632-1640 - [c191]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: 33-43 - [c190]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: 1301-1310 - [i56]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 abs/2201.01449 (2022) - [i55]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 abs/2207.10062 (2022) - [i54]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 abs/2207.11166 (2022) - [i53]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 abs/2208.13027 (2022) - 2021
- [j30]Michael Ko, Emma Chen, Ashwin Agrawal, Pranav Rajpurkar, Anand Avati, Andrew Yan-Tak Ng, Sanjay Basu, Nigam H. Shah:
Improving hospital readmission prediction using individualized utility analysis. J. Biomed. Informatics 119: 103826 (2021) - [j29]Sharon Zhou, Jiequan Zhang, Hang Jiang, Torbjörn Lundh, Andrew Y. Ng:
Data augmentation with Mobius transformations. Mach. Learn. Sci. Technol. 2(2): 25016 (2021) - [j28]David Eng, Christopher 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) - [c189]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: 105-115 - [c188]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: 116-124 - [c187]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: 125-132 - [c186]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 - [c185]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: 519-528 - [c184]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: 190-204 - [c183]Siyu Shi, Ishaan Malhi, Kevin Tran, Andrew Y. Ng, Pranav Rajpurkar:
Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays. MIDL 2021: 699-712 - [c182]Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng, Pranav Rajpurkar:
MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. MIDL 2021: 728-744 - [c181]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: 156-167 - [c180]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: 209-219 - [c179]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: 103-125 - [c178]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: 755-769 - [c177]Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven Q. H. Truong, Du Nguyen Duong, Tan Bui, Pierre J. 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 - [c176]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 - [i52]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 abs/2101.06871 (2021) - [i51]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 abs/2102.08660 (2021) - [i50]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 abs/2102.10484 (2021) - [i49]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 abs/2102.10663 (2021) - [i48]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 abs/2102.11467 (2021) - [i47]Siyu Shi, Ishaan Malhi, Kevin Tran, Andrew Y. Ng, Pranav Rajpurkar:
CheXseen: Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays. CoRR abs/2103.04590 (2021) - [i46]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 abs/2103.09957 (2021) - [i45]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 abs/2103.14339 (2021) - [i44]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 abs/2104.00793 (2021) - [i43]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 abs/2105.02489 (2021) - [i42]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 abs/2106.04452 (2021) - [i41]Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven Q. H. Truong, Du Nguyen Duong, Tan Bui, Pierre J. Chambon, Yuhao Zhang, Matthew P. Lungren, Andrew Y. Ng, Curtis P. Langlotz, Pranav Rajpurkar:
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports. CoRR abs/2106.14463 (2021) - [i40]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 abs/2108.01764 (2021) - 2020
- [j27]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, 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) - [j26]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, 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) - [j25]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) - [j24]Pranav Rajpurkar, Chloe P. 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) - [c175]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: 212-218 - [c174]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: 267-276 - [c173]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: 1500-1519 - [c172]Tony Duan, Anand Avati, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler:
NGBoost: Natural Gradient Boosting for Probabilistic Prediction. ICML 2020: 2690-2700 - [c171]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: 318-327 - [i39]Sharon Zhou, Jiequan Zhang, Hang Jiang, Torbjörn Lundh, Andrew Y. Ng:
Data augmentation with Möbius transformations. CoRR abs/2002.02917 (2020) - [i38]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 abs/2002.11379 (2020) - [i37]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 abs/2004.09167 (2020) - [i36]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 abs/2004.09754 (2020) - [i35]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 abs/2005.03743 (2020) - [i34]Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Stefano Ermon:
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology. CoRR abs/2006.03680 (2020) - [i33]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 abs/2007.06199 (2020) - [i32]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 abs/2009.08123 (2020) - [i31]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 abs/2010.04715 (2020) - [i30]Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng, Pranav Rajpurkar:
MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. CoRR abs/2010.05352 (2020) - [i29]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 abs/2010.15269 (2020) - [i28]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 abs/2011.05479 (2020) - [i27]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 abs/2011.06129 (2020) - [i26]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 abs/2011.07227 (2020)
2010 – 2019
- 2019
- [c170]Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Christopher 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: 590-597 - [c169]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: 1909-1916 - [c168]Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng:
Countdown Regression: Sharp and Calibrated Survival Predictions. UAI 2019: 145-155 - [i25]Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Christopher 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 abs/1901.07031 (2019) - [i24]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 abs/1906.05433 (2019) - [i23]Tony Duan, Anand Avati, Daisy Yi Ding, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler:
NGBoost: Natural Gradient Boosting for Probabilistic Prediction. CoRR abs/1910.03225 (2019) - 2018
- [j23]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): 55-64 (2018) - [c167]Ziang Xie, Guillaume Genthial, Stanley Xie, Andrew Y. Ng, Dan Jurafsky:
Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction. NAACL-HLT 2018: 619-628 - [i22]Anand Avati, Tony Duan, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng:
Countdown Regression: Sharp and Calibrated Survival Predictions. CoRR abs/1806.08324 (2018) - [i21]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 abs/1812.00371 (2018) - 2017
- [j22]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: 195-213 (2017) - [j21]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): 159:1-159:23 (2017) - [c166]Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah:
Improving palliative care with deep learning. BIBM 2017: 311-316 - [c165]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 - [c164]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: 195-204 - [r4]Adam Coates, Pieter Abbeel, Andrew Y. Ng:
Autonomous Helicopter Flight Using Reinforcement Learning. Encyclopedia of Machine Learning and Data Mining 2017: 75-85 - [r3]Pieter Abbeel, Andrew Y. Ng:
Inverse Reinforcement Learning. Encyclopedia of Machine Learning and Data Mining 2017: 678-682 - [i20]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 abs/1703.02573 (2017) - [i19]Pranav Rajpurkar, Awni Y. Hannun, Masoumeh Haghpanahi, Codie Bourn, Andrew Y. Ng:
Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks. CoRR abs/1707.01836 (2017) - [i18]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 abs/1711.05225 (2017) - [i17]Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah:
Improving Palliative Care with Deep Learning. CoRR abs/1711.06402 (2017) - [i16]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 abs/1712.06957 (2017) - 2016
- [j20]Michiel Kallenberg, Kersten Petersen, Mads Nielsen, Andrew Y. Ng, Pengfei Diao, Christian Igel, Celine M. Vachon, Katharina Holland, Rikke Rass Winkel, Nico Karssemeijer, Martin Lillholm:
Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring. IEEE Trans. Medical Imaging 35(5): 1322-1331 (2016) - [c163]Andrew Y. Ng:
Deep Learning: What's Next. AAMAS 2016: 1 - [c162]