Marzyeh Ghassemi

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 139

Top Venues

Massachusetts Institute of Technology, Cambridge, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, USA

PHD

Publications

Saachi Jain, Kimia Hamidieh, Kristian Georgiev, Andrew Ilyas, Marzyeh Ghassemi, Aleksander Madry
Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection. CoRR (2024)
Niklas Mannhardt, Elizabeth Bondi-Kelly, Barbara Lam, Chloe O'Connell, Mercy Asiedu, Hussein Mozannar, Monica Agrawal, Alejandro Buendia, Tatiana Urman, Irbaz B. Riaz, Catherine E. Ricciardi, Marzyeh Ghassemi, David A. Sontag
Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study. CoRR (2024)
Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
Asymmetry in Low-Rank Adapters of Foundation Models. CoRR (2024)
Nathan Ng, Roger B. Grosse, Marzyeh Ghassemi
Measuring Stochastic Data Complexity with Boltzmann Influence Functions. CoRR (2024)
Saadia Gabriel, Isha Puri, Xuhai Xu, Matteo Malgaroli, Marzyeh Ghassemi
Can AI Relate: Testing Large Language Model Response for Mental Health Support. CoRR (2024)
Kyle O'Brien, Nathan Ng, Isha Puri, Jorge Mendez, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi, Thomas Hartvigsen
Improving Black-box Robustness with In-Context Rewriting. CoRR (2024)
Adiba Orzikulova, Han Xiao, Zhipeng Li, Yukang Yan, Yuntao Wang, Yuanchun Shi, Marzyeh Ghassemi, Sung-Ju Lee, Anind K. Dey, Xuhai Xu
Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention. CHI (2024)
Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan, Marzyeh Ghassemi
Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation. ICLR (2024)
Adiba Orzikulova, Han Xiao, Zhipeng Li, Yukang Yan, Yuntao Wang, Yuanchun Shi, Marzyeh Ghassemi, Sung-Ju Lee, Anind K. Dey, Xuhai "Orson" Xu
Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention. CoRR (2024)
David Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White
Application-Driven Innovation in Machine Learning. CoRR (2024)
Kumail Alhamoud, Yasir Ghunaim, Motasem Alfarra, Thomas Hartvigsen, Philip Torr, Bernard Ghanem, Adel Bibi, Marzyeh Ghassemi
FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging. CoRR (2024)
Haoran Zhang, Aparna Balagopalan, Nassim Oufattole, Hyewon Jeong, Yan Wu, Jiacheng Zhu, Marzyeh Ghassemi
LEMoN: Label Error Detection using Multimodal Neighbors. CoRR (2024)
Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan, Marzyeh Ghassemi
Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation. CoRR (2024)
Xuhai Xu, Bingsheng Yao, Yuanzhe Dong, Saadia Gabriel, Hong Yu, James A. Hendler, Marzyeh Ghassemi, Anind K. Dey, Dakuo Wang
Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 8 (1) (2024)
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai "Orson" Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR (2024)
Hyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi
Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals. MLHC (2023)
Yuzhe Yang, Haoran Zhang, Dina Katabi, Marzyeh Ghassemi
Change is Hard: A Closer Look at Subpopulation Shift. ICML (2023)
Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger B. Grosse, Alireza Makhzani
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. CoRR (2023)
Hyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi
Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals. CoRR (2023)
Jiyoung Lee, Seungho Kim, Seunghyun Won, Joonseok Lee, Marzyeh Ghassemi, James Thorne, Jaeseok Choi, O.-Kil Kwon, Edward Choi
VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perception. CoRR (2023)
Hyewon Jeong, Nassim Oufattole, Aparna Balagopalan, Matthew B. A. McDermott, Payal Chandak, Marzyeh Ghassemi, Collin M. Stultz
Event-Based Contrastive Learning for Medical Time Series. CoRR (2023)
Taylor W. Killian, Sonali Parbhoo, Marzyeh Ghassemi
Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning. CoRR (2023)
Yuzhe Yang, Haoran Zhang, Dina Katabi, Marzyeh Ghassemi
Change is Hard: A Closer Look at Subpopulation Shift. CoRR (2023)
Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. ICML (2023)
Yuzhe Yang, Haoran Zhang, Judy W. Gichoya, Dina Katabi, Marzyeh Ghassemi
The Limits of Fair Medical Imaging AI In The Wild. CoRR (2023)
Yuxin Xiao, Shulammite Lim, Tom Joseph Pollard, Marzyeh Ghassemi
In the Name of Fairness: Assessing the Bias in Clinical Record De-identification. CoRR (2023)
Taylor W. Killian, Sonali Parbhoo, Marzyeh Ghassemi
Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023)
Elizabeth Bondi-Kelly, Thomas Hartvigsen, Lindsay M. Sanneman, Swami Sankaranarayanan, Zach Harned, Grace Wickerson, Judy Wawira Gichoya, Lauren Oakden-Rayner, Leo Anthony Celi, Matthew P. Lungren, Julie A. Shah, Marzyeh Ghassemi
Taking Off with AI: Lessons from Aviation for Healthcare. EAAMO (2023)
Ming-Ying Yang, Gloria Hyun-Jung Kwak, Tom J. Pollard, Leo Anthony Celi, Marzyeh Ghassemi
Evaluating the Impact of Social Determinants on Health Prediction. CoRR (2023)
Paula Dhiman, Rebecca Whittle, Ben Van Calster, Marzyeh Ghassemi, Xiaoxuan Liu, Melissa D. McCradden, Karel G. M. Moons, Richard D. Riley, Gary S. Collins
The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols. Nat. Mac. Intell. 5 (8) (2023)
Vinith Menon Suriyakumar, Marzyeh Ghassemi, Berk Ustun
When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction. ICML (2023)
Qixuan Jin, Jacobien H. F. Oosterhoff, Yepeng Huang, Marzyeh Ghassemi, Gabriel A Brat
Clinical Relevance Score for Guided Trauma Injury Pattern Discovery with Weakly Supervised β-VAE. CHIL (2023)
Ming-Ying Yang, Gloria Hyun-Jung Kwak, Tom J. Pollard, Leo Anthony Celi, Marzyeh Ghassemi
Evaluating the Impact of Social Determinants on Health Prediction in the Intensive Care Unit. AIES (2023)
Anja Thieme, Aditya V. Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger
Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward. CHI Extended Abstracts (2023)
Jiyoung Lee, Seungho Kim, Seunghyun Won, Joonseok Lee, Marzyeh Ghassemi, James Thorne, Jaeseok Choi, O.-Kil Kwon, Edward Choi
VisAlign: Dataset for Measuring the Alignment between AI and Humans in Visual Perception. NeurIPS (2023)
Tom Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors. NeurIPS (2023)
Yuxin Xiao, Shulammite Lim, Tom Joseph Pollard, Marzyeh Ghassemi
In the Name of Fairness: Assessing the Bias in Clinical Record De-identification. FAccT (2023)
Nathan H. Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi
Predicting Out-of-Domain Generalization with Neighborhood Invariance. Trans. Mach. Learn. Res. 2023 (2023)
Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B. Grosse
If Influence Functions are the Answer, Then What is the Question? NeurIPS (2022)
Minfan Zhang, Daniel Ehrmann, Mjaye Mazwi, Danny Eytan, Marzyeh Ghassemi, Fanny Chevalier
Get To The Point! Problem-Based Curated Data Views To Augment Care For Critically Ill Patients. CHI (2022)
Marzyeh Ghassemi, Shakir Mohamed
Machine learning and health need better values. npj Digit. Medicine 5 (2022)
Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz, Marzyeh Ghassemi
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations. CoRR (2022)
Nathan Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi
Predicting Out-of-Domain Generalization with Local Manifold Smoothness. CoRR (2022)
Natalie Dullerud, Karsten Roth, Kimia Hamidieh, Nicolas Papernot, Marzyeh Ghassemi
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning. ICLR (2022)
Azadeh Assadi, Peter C. Laussen, Gabrielle Freire, Marzyeh Ghassemi, Patricia Trbovich
Decision-centered design of a clinical decision support system for acute management of pediatric congenital heart disease. Frontiers Digit. Health 4 (2022)
Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg
Uniform Priors for Data-Efficient Learning. CVPR Workshops (2022)
Vinith M. Suriyakumar, Marzyeh Ghassemi, Berk Ustun
When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction. CoRR (2022)
Natalie Dullerud, Karsten Roth, Kimia Hamidieh, Nicolas Papernot, Marzyeh Ghassemi
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning. CoRR (2022)
Hammaad Adam, Ming-Ying Yang, Kenrick Cato, Ioana Baldini, Charles Senteio, Leo Anthony Celi, Jiaming Zeng, Moninder Singh, Marzyeh Ghassemi
Write It Like You See It: Detectable Differences in Clinical Notes by Race Lead to Differential Model Recommendations. AIES (2022)
Mehdi Fatemi, Mary Wu, Jeremy Petch, Walter Nelson, Stuart J. Connolly, Alexander Benz, Anthony Carnicelli, Marzyeh Ghassemi
Semi-Markov Offline Reinforcement Learning for Healthcare. CoRR (2022)
Sarah M. Goodday, E. Karlin, A. Brooks, C. Chapman, Daniel R. Karlin, Luca Foschini, E. Kipping, M. Wildman, M. Francis, H. Greenman, Li Li, Eric E. Schadt, Marzyeh Ghassemi, Anna Goldenberg, Francesca Cormack, N. Taptiklis, C. Centen, S. Smith, Stephen H. Friend
Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum. npj Digit. Medicine 5 (2022)
Jimmy Ba, Murat A. Erdogdu, Marzyeh Ghassemi, Shengyang Sun, Taiji Suzuki, Denny Wu, Tianzong Zhang
Understanding the Variance Collapse of SVGD in High Dimensions. ICLR (2022)
Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse, Alireza Makhzani
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. ICLR (2022)
Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. CoRR (2022)
Hammaad Adam, Ming-Ying Yang, Kenrick Cato, Ioana Baldini, Charles Senteio, Leo Anthony Celi, Jiaming Zeng, Moninder Singh, Marzyeh Ghassemi
Write It Like You See It: Detectable Differences in Clinical Notes By Race Lead To Differential Model Recommendations. CoRR (2022)
Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Pfohl, Marzyeh Ghassemi
Improving the Fairness of Chest X-ray Classifiers. CHIL (2022)
Taylor W. Killian, Marzyeh Ghassemi, Shalmali Joshi
Counterfactually Guided Policy Transfer in Clinical Settings. CHIL (2022)
Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Robert Pfohl, Marzyeh Ghassemi
Improving the Fairness of Chest X-ray Classifiers. CoRR (2022)
Marzyeh Ghassemi, Elaine O. Nsoesie
In medicine, how do we machine learn anything real? Patterns 3 (1) (2022)
Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz, Marzyeh Ghassemi
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations. FAccT (2022)
Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B. Grosse
If Influence Functions are the Answer, Then What is the Question? CoRR (2022)
Mehdi Fatemi, Mary Wu, Jeremy Petch, Walter Nelson, Stuart J. Connolly, Alexander Benz, Anthony Carnicelli, Marzyeh Ghassemi
Semi-Markov Offline Reinforcement Learning for Healthcare. CHIL (2022)
Thomas Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors. CoRR (2022)
Sindhu C. M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. CoRR (2021)
Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi
A comprehensive EHR timeseries pre-training benchmark. CHIL (2021)
Sindhu C. M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. CIKM (2021)
Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew B. A. McDermott, Irene Y. Chen, Marzyeh Ghassemi
CheXclusion: Fairness gaps in deep chest X-ray classifiers. PSB (2021)
Victoria Cheng, Vinith M. Suriyakumar, Natalie Dullerud, Shalmali Joshi, Marzyeh Ghassemi
Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness. FAccT (2021)
Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. NeurIPS (2021)
Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. CoRR (2021)
Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi
An Empirical Framework for Domain Generalization in Clinical Settings. CoRR (2021)
Mehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi
Medical Dead-ends and Learning to Identify High-Risk States and Treatments. NeurIPS (2021)
Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi
Learning Optimal Predictive Checklists. CoRR (2021)
Imon Banerjee, Ananth Reddy Bhimireddy, John L. Burns, Leo Anthony Celi, Li-Ching Chen, Ramon Correa, Natalie Dullerud, Marzyeh Ghassemi, Shih-Cheng Huang, Po-Chih Kuo, Matthew P. Lungren, Lyle J. Palmer, Brandon J. Price, Saptarshi Purkayastha, Ayis Pyrros, Luke Oakden-Rayner, Chima Okechukwu, Laleh Seyyed-Kalantari, Hari Trivedi, Ryan Wang, Zachary Zaiman, Haoran Zhang, Judy W. Gichoya
Reading Race: AI Recognises Patient's Racial Identity In Medical Images. CoRR (2021)
Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi
An empirical framework for domain generalization in clinical settings. CHIL (2021)
Karsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi
Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. ICML (2021)
Mehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi
Medical Dead-ends and Learning to Identify High-risk States and Treatments. CoRR (2021)
Suchi Saria, Marzyeh Ghassemi, Ziad Obermeyer, Karandeep Singh, Pei-Yun S. Hsueh, Eric Topol
Making Health AI Work in the Real World: Strategies, innovations, and best practices for using AI to improve care delivery. AMIA (2021)
Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi
Learning Optimal Predictive Checklists. NeurIPS (2021)
Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. FAccT (2021)
Zining Zhu, Aparna Balagopalan, Marzyeh Ghassemi, Frank Rudzicz
Quantifying the Task-Specific Information in Text-Based Classifications. CoRR (2021)
Susanne Gaube, Harini Suresh, Martina Raue, Alexander Merritt, Seth J. Berkowitz, Eva Lermer, Joseph F. Coughlin, John V. Guttag, Errol Colak, Marzyeh Ghassemi
Do as AI say: susceptibility in deployment of clinical decision-aids. npj Digit. Medicine 4 (2021)
Stephen R. Pfohl, Haoran Zhang, Yizhe Xu, Agata Foryciarz, Marzyeh Ghassemi, Nigam H. Shah
A comparison of approaches to improve worst-case predictive model performance over patient subpopulations. CoRR (2021)
Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi
Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings. CoRR (2020)
Irene Y. Chen, Emma Pierson, Sherri Rose, Shalmali Joshi, Kadija Ferryman, Marzyeh Ghassemi
Ethical Machine Learning in Health Care. CoRR (2020)
Matthew B. A. McDermott, Tzu-Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits
CheXpert++: Approximating the CheXpert Labeler for Speed, Differentiability, and Probabilistic Output. MLHC (2020)
Nathan Ng, Kyunghyun Cho, Marzyeh Ghassemi
SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness. CoRR (2020)
Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan, Marzyeh Ghassemi, Michael C. Hughes, Tristan Naumann
MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III. CHIL (2020)
Bret Nestor, Liam G. McCoy, Amol Verma, Chloé Pou-Prom, Joshua Murray, Sebnem Kuzulugil, David Dai, Muhammad Mamdani, Anna Goldenberg, Marzyeh Ghassemi
Preparing a Clinical Support Model for Silent Mode in General Internal Medicine. MLHC (2020)
Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi
Hurtful words: quantifying biases in clinical contextual word embeddings. CHIL (2020)
Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare. ML4H@NeurIPS (2020)
Alister D. Costa, Stefan Denkovski, Michal Malyska, Sae Young Moon, Brandon Rufino, Zhen Yang, Taylor W. Killian, Marzyeh Ghassemi
Multiple Sclerosis Severity Classification From Clinical Text. ClinicalNLP@EMNLP (2020)
Matthew B. A. McDermott, Tzu-Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits
CheXpert++: Approximating the CheXpert labeler for Speed, Differentiability, and Probabilistic Output. CoRR (2020)
Karsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi
S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. CoRR (2020)
Joseph Paul Cohen, Lan Dao, Paul Morrison, Karsten Roth, Yoshua Bengio, Beiyi Shen, Almas Abbasi, Mahsa Hoshmand-Kochi, Marzyeh Ghassemi, Haifang Li, Tim Q. Duong
Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning. CoRR (2020)
Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data. CoRR (2020)
Shirly Wang, Seung Eun Yi, Shalmali Joshi, Marzyeh Ghassemi
Confounding Feature Acquisition for Causal Effect Estimation. ML4H@NeurIPS (2020)
Nathan Ng, Marzyeh Ghassemi, Narendran Thangarajan, Jiacheng Pan, Qi Guo
Improving Dialogue Breakdown Detection with Semi-Supervised Learning. CoRR (2020)
Alister D. Costa, Stefan Denkovski, Michal Malyska, Sae Young Moon, Brandon Rufino, Zhen Yang, Taylor W. Killian, Marzyeh Ghassemi
Multiple Sclerosis Severity Classification From Clinical Text. CoRR (2020)
Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Marzyeh Ghassemi