Chayes, Jennifer
University of California, Berkeley
7 papers on CoChatORCID 0000-0003-4020-8618
Most cited papers
- Verified
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
De-Arteaga, M., Romanov, A., Wallach, H., Chayes, J., Borgs, C., Chouldechova, A., Geyik, S., Kenthapadi, K., & Kalai, A. T. (2019) · arXiv
Ethics and Social Impacts of AINames, Identity, and Discrimination Research
Cited by 337
- Verified
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
De-Arteaga, M., Romanov, A., Wallach, H., Chayes, J., Borgs, C., Chouldechova, A., Geyik, S., Kenthapadi, K., & Kalai, A. T. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency
Ethics and Social Impacts of AINames, Identity, and Discrimination Research
Cited by 337
- Verified
Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys
Climate Change and Environmental ImpactArtificial Intelligence Applications
Cited by 336
- Verified
ChatGPT Research Group for Optimizing the Crystallinity of MOFs and COFs
Zheng, Z., Zhang, O., Nguyen, H. L., Rampal, N., Alawadhi, A. H., Rong, Z., Head-Gordon, T., Borgs, C., Chayes, J. T., & Yaghi, O. M. (2023) · ACS Central Science
Machine Learning in Materials ScienceMetal-Organic Frameworks: Synthesis and Applications
Cited by 172
- Verified
Large language models for reticular chemistry
Zheng, Z., Rampal, N., Inizan, T. J., Borgs, C., Chayes, J. T., & Yaghi, O. M. (2025) · Nature Reviews Materials
Machine Learning in Materials ScienceMetal-Organic Frameworks: Synthesis and Applications
Cited by 134
- Verified
Optimal Multiperiod Pricing with Service Guarantees
Borgs, C., Candogan, O., Chayes, J., Lobel, I., & Nazerzadeh, H. (2014) · Management Science
Supply Chain and Inventory ManagementConsumer Market Behavior and Pricing
Cited by 60
- Verified
A multi-grained symmetric differential equation model for learning protein-ligand binding dynamics
Liu, S., Du, W., Xu, H., Li, Y., Li, Z., Bhethanabotla, V., Yan, D., Borgs, C., Anandkumar, A., Guo, H., et al. (2025) · Nature Communications
Computational Drug Discovery MethodsProtein Structure and Dynamics
Cited by 6
Go further with a free account
Verify every reference, keep papers in a library, and ask questions across them.
Sign up - it is free