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ORCIDVishwali Mhasawade
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2020 – today
- 2025
[c9]Vishwali Mhasawade, Rumi Chunara:
Disparate Effect Of Missing Mediators On Transportability of Causal Effects. CLeaR 2025: 757-771- [i11]Stefan Hegselmann, Helen Zhou, Elizabeth Healey, Trenton Chang, Caleb Ellington, Vishwali Mhasawade, Sana Tonekaboni, Peniel N. Argaw, Haoran Zhang:
Machine Learning for Health symposium 2024 - Findings track. CoRR abs/2503.00984 (2025) - [i10]Stephen R. Pfohl, Natalie Harris, Chirag Nagpal, David Madras, Vishwali Mhasawade, Olawale Salaudeen, Awa Dieng, Shannon Sequeira, Santiago Eduardo Arciniegas, Lillian Sung, Nnamdi Ezeanochie, Heather Cole-Lewis, Katherine A. Heller, Sanmi Koyejo, Alexander D'Amour:
Understanding challenges to the interpretation of disaggregated evaluations of algorithmic fairness. CoRR abs/2506.04193 (2025) - 2024
- [c8]Vishwali Mhasawade
, Alexander D'Amour, Stephen R. Pfohl:
A Causal Perspective on Label Bias. FAccT 2024: 1282-1294 - [c7]Vishwali Mhasawade, Salman Rahman, Zoé Haskell-Craig, Rumi Chunara:
Understanding Disparities in Post Hoc Machine Learning Explanation. FAccT 2024: 2374-2388 - [c6]Helen Zhou, Stefan Hegselmann, Elizabeth Healey, Trenton Chang, Caleb Ellington, Michael Leone, Vishwali Mhasawade, Sana Tonekaboni, Winston Chen, Hyewon Jeong, Xiaoxiao Li, Juyeon Heo, Payal Chandak, Ayush Noori, Sarah Jabbour, Jessica Dafflon, Jerry Ji, Jivat Neet Kaur, Amin Adibi, Xu Cao, Meera Krishnamoorthy, Yidi Huang, Fabian Gröger, Aishwarya Mandyam, Niloufar Saharhkhiz, Teya S. Bergamaschi, William Boag, Jeroen Berrevoets, Matthew Lee, Kyle Heuton, Peniel N. Argaw, Haoran Zhang:
Machine Learning for Health (ML4H) 2024. ML4H@NeurIPS 2024: 1-13 - [e1]Stefan Hegselmann, Helen Zhou, Elizabeth Healey, Trenton Chang, Caleb Ellington, Vishwali Mhasawade, Sana Tonekaboni, Peniel N. Argaw, Haoran Zhang:
Machine Learning for Health, ML4H@NeurIPS 2024, Vancouver, Canada, 15-16 December 2024. Proceedings of Machine Learning Research 259, PMLR 2024 [contents] - [i9]Vishwali Mhasawade, Salman Rahman, Zoe Haskell-Craig, Rumi Chunara:
Understanding Disparities in Post Hoc Machine Learning Explanation. CoRR abs/2401.14539 (2024) - [i8]Miao Zhang, Salman Rahman, Vishwali Mhasawade, Rumi Chunara:
Impact on Public Health Decision Making by Utilizing Big Data Without Domain Knowledge. CoRR abs/2402.06059 (2024) - [i7]Vishwali Mhasawade, Rumi Chunara:
Disparate Effect Of Missing Mediators On Transportability of Causal Effects. CoRR abs/2403.08638 (2024) - 2023
- [c5]Vishwali Mhasawade:
Advancing Health Equity with Machine Learning. AIES 2023: 955-956 - [c4]Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Kristen Severson, Mercy Nyamewaa Asiedu, Serina Chang, Bonaventure F. P. Dossou, Qian Huang, Fahad Kamran, Haoran Zhang, Sujay Nagaraj, Luis Oala, Shan Xu, Chinasa T. Okolo, Helen Zhou, Jessica Dafflon, Caleb Ellington, Sarah Jabbour, Hyewon Jeong, Harry Reyes Nieva, Yuzhe Yang, Ghada Zamzmi, Vishwali Mhasawade, Van Truong, Payal Chandak, Matthew Lee, Peniel N. Argaw, Kyle Heuton, Harvineet Singh, Thomas Hartvigsen:
Machine Learning for Health (ML4H) 2023. ML4H@NeurIPS 2023: 1-12 - 2021
- [j1]Vishwali Mhasawade, Yuan Zhao, Rumi Chunara:
Machine learning and algorithmic fairness in public and population health. Nat. Mach. Intell. 3(8): 659-666 (2021) - [c3]Vishwali Mhasawade, Rumi Chunara:
Causal Multi-level Fairness. AIES 2021: 784-794 - [c2]Harvineet Singh, Rina Singh, Vishwali Mhasawade, Rumi Chunara:
Fairness Violations and Mitigation under Covariate Shift. FAccT 2021: 3-13 - 2020
- [c1]Vishwali Mhasawade, Nabeel Abdur Rehman, Rumi Chunara:
Population-aware hierarchical bayesian domain adaptation via multi-component invariant learning. CHIL 2020: 182-192 - [i6]Vishwali Mhasawade, Yuan Zhao, Rumi Chunara:
Machine Learning in Population and Public Health. CoRR abs/2008.07278 (2020) - [i5]Vishwali Mhasawade, Rumi Chunara:
Causal Multi-Level Fairness. CoRR abs/2010.07343 (2020)
2010 – 2019
- 2019
- [i4]Vishwali Mhasawade, Nabeel Abdur Rehman, Rumi Chunara:
Population-aware Hierarchical Bayesian Domain Adaptation via Multiple-component Invariant Learning. CoRR abs/1908.09222 (2019) - [i3]Harvineet Singh, Rina Singh, Vishwali Mhasawade, Rumi Chunara:
Fair Predictors under Distribution Shift. CoRR abs/1911.00677 (2019) - 2018
- [i2]Vishwali Mhasawade, Ildikó Emese Szabó, Melanie Tosik, Sheng-Fu Wang:
Neural Networks and Quantifier Conservativity: Does Data Distribution Affect Learnability? CoRR abs/1809.05733 (2018) - [i1]Vishwali Mhasawade, Nabeel Abdur Rehman, Rumi Chunara:
Population-aware Hierarchical Bayesian Domain Adaptation. CoRR abs/1811.08579 (2018)
Coauthor Index
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