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ORCIDMegan Richards
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2020 – today
- 2024
[c3]Megan Richards, Polina Kirichenko, Diane Bouchacourt, Mark Ibrahim:
Does Progress On Object Recognition Benchmarks Improve Generalization on Crowdsourced, Global Data? ICLR 2024- [i5]Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra:
An Introduction to Vision-Language Modeling. CoRR abs/2405.17247 (2024) - [i4]Abhishek Sureddy, Dishant Padalia, Nandhinee Periyakaruppa, Oindrila Saha, Adina Williams, Adriana Romero-Soriano, Megan Richards, Polina Kirichenko, Melissa Hall:
Decomposed evaluations of geographic disparities in text-to-image models. CoRR abs/2406.11988 (2024) - 2023
- [c2]Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim:
Exploring Why Object Recognition Performance Degrades Across Income Levels and Geographies with Factor Annotations. NeurIPS 2023 - [i3]Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim:
Pinpointing Why Object Recognition Performance Degrades Across Income Levels and Geographies. CoRR abs/2304.05391 (2023) - [i2]Megan Richards, Polina Kirichenko, Diane Bouchacourt, Mark Ibrahim:
Does Progress On Object Recognition Benchmarks Improve Real-World Generalization? CoRR abs/2307.13136 (2023) - 2022
- [c1]Mark P. Sendak, Gaurav Sirdeshmukh, Timothy Ochoa, Hayley Premo, Linda Tang, Kira Niederhoffer, Sarah Reed, Kaivalya Deshpande, Emily Sterrett, Melissa Bauer, Laurie Snyder, Afreen Shariff, David Whellan, Jeffrey Riggio, David Gaieski, Kristin Corey, Megan Richards, Michael Gao, Marshall Nichols, Bradley Heintze, William Knechtle, William Ratliff, Suresh Balu:
Development and Validation of ML-DQA - a Machine Learning Data Quality Assurance Framework for Healthcare. MLHC 2022: 741-759 - [i1]Mark P. Sendak
, Gaurav Sirdeshmukh, Timothy Ochoa, Hayley Premo, Linda Tang, Kira Niederhoffer, Sarah Reed, Kaivalya Deshpande, Emily Sterrett, Melissa Bauer, Laurie Snyder, Afreen Shariff, David Whellan, Jeffrey Riggio, David Gaieski, Kristin Corey, Megan Richards, Michael Gao, Marshall Nichols, Bradley Heintze, William Knechtle, William Ratliff, Suresh Balu:
Development and Validation of ML-DQA - a Machine Learning Data Quality Assurance Framework for Healthcare. CoRR abs/2208.02670 (2022)
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