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James Day, Olivia Verdugo, Markus Spiske on Unsplash
James Day, Olivia Verdugo, Markus Spiske on Unsplash
Singh, Abhishek, et al. "CoDream: Exchanging dreams instead of models for federated aggregation with heterogeneous models." Proceedings of AAAI. 2025
Lu, Charles, et al. "Data Acquisition via Experimental Design for Decentralized Data Markets." arXiv preprint arXiv:2403.13893 (2024).
Gabriela Torres Vives, et al. "Enhancing the Privacy of a Digital Pound." Bank of England and MIT Digital Currency Initiative, December 2024
Abhishek Singh, Split Inference - Metrics, Benchmarks and Algorithms, ECCV'24
Zaid Tasneem, DecentNeRFs: Decentralized Neural Radiance Fields from Crowdsourced Images, ECCV'24
Garg, Aditi, and Ayush Chopra. "Distributed Calibration of Agent-based Models." epiDAMIK 2024: The 7th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery at KDD 2024. 2024.
Roeder, G., Das, M., Saadi, J.I., Harrington, C., Verma, A., Breazeal, C., D’Ignazio, C., Yang, M., & Ostrowski, A.K. 2024. Building spaces for design justice: A case study on the design justice pedagogy summit. Accepted to ASME 2024 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE2024).
Whitepaper
Ostrowski, A.K., Das, M., Roeder, G., Saadi. J.I., Harrington, C., Verma, A., Breazeal, C., D’Ignazio, C., & Yang, M. 2024. Supporting reflexivity and action on equity and justice in design education: Insights from the design justice pedagogy summit. Design Thinking Research Symposium (DTRS) 14.
Bao, C. (2024). Mitigating Undercutting Attacks: A Study on Mining and Transaction Fee Behavior. [Master's thesis, MIT]. https://media.mit.edu/publications/mitigating-undercutting-attacks-a-study-on-mining-and-transaction-fee-behavior
Chopra, Ayush, et al. "flame: A Framework for Learning in Agent-based ModEls." Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems. 2024.
Singh, Abhishek, et al. "Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release." Advances in Neural Information Processing Systems 36 (2024).
Chopra, Ayush, et al. "Private agent-based modeling." In Proceedings of Autonomous Agents and Multi-agent Systems (AAMAS) 2024
Gupta, G., Kapila, R., Chopra, A., & Raskar, R. (2024). First 100 days of pandemic; an interplay of pharmaceutical, behavioral and digital interventions--A study using agent based modeling. Proceedings of Autonomous Agents and Multi-agent Systems (AAMAS) 2024
Chopra, Quera-bofarull and Zhang. "Differentiable Agent-based Modeling: Systems, Methods and Applications". Tutorial at 23rd Autonomous Agents and Multi-agent Systems (AAMAS) 2024.
Artificial Intelligence (cs.AI), arXiv:2403.04893 [cs.AI] (or arXiv:2403.04893v1 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2403.04893 | Shayne Longpre* 1 Sayash Kapoor** 2 Kevin Klyman** 3 Ashwin Ramaswami 4 Rishi Bommasani 3 Borhane Blili-Hamelin 5 Yangsibo Huang 2 Aviya Skowron 6 Zheng-Xin Yong 7 Suhas Kotha 8 Yi Zeng 9 Weiyan Shi 10 Xianjun Yang 11 Reid Southen Alexander Robey
Alex Berke, Tobin South, Robert Mahari, Kent Larson, and Alex Pentland. 2024. Poster: zkTax: A Pragmatic Way to Support Zero-Knowledge Tax Disclosures. In Proceedings of Conference on Computer and Communications Security (CCS’24). ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3658644.3691421
Chopra, Ayush, et al. "Using neural networks to calibrate agent based models enables improved regional evidence for vaccine strategy and policy." Vaccine 41.48 (2023): 7067-7071.
Hawkins, R.D., Berdahl, A.M., Pentland, A.‘. et al. Flexible social inference facilitates targeted social learning when rewards are not observable. Nat Hum Behav (2023). https://doi.org/10.1038/s41562-023-01682-x
E. C. Ferrer, I. Berman, A. Kapitonov, V. Manaenko, M. Chernyaev and P. Tarasov, "Gaka-Chu: A Self-Employed Autonomous Robot Artist," 2023 IEEE International Conference on Robotics and Automation (ICRA), London, United Kingdom, 2023, pp. 11583-11589, doi: 10.1109/ICRA48891.2023.10160866.
Bühler, M. et al., 2023. Harnessing Digital Federation Platforms and Data Cooperatives to Empower SMEs and Local Small Communities, OBSERVER RESEARCH FOUNDATION. India.
Bahrami, Mohsen, et al. "Predicting merchant future performance using privacy-safe network-based features." Scientific Reports 13.1 (2023): 10073.
Chopra, Ayush, et al. "Differentiable agent-based epidemiology." Proceedings of 22nd International Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2023)
Quera-Bofarull, A., Chopra, A., Aylett-Bullock, J., Cuesta-Lazaro, C., Calinescu, A., Raskar, R., & Wooldridge, M. (2023). Don’t simulate twice: One-shot sensitivity analyses via automatic differentiation. Proceedings of Autonomous Agents and Multi-agent Systems (AAMAS 2023)
Epstein Z and Hause L. Yourfeed: Towards open science and interoperable systems for social media. arXiv.
Chopra, Ayush, et al. "Learning to censor by noisy sampling." European Conference on Computer Vision. Cham: Springer Nature Switzerland, 2022.
Chopra, Ayush, et al. "DeepABM: scalable, efficient and differentiable agent-based simulations via graph neural networks." Winter Simulation Conference 2021
Romero-Brufau, S., Chopra, A., Ryu, A. J., Gel, E., Raskar, R., Kremers, W., ... & Kingsley, T. C. (2021). Public health impact of delaying second dose of BNT162b2 or mRNA-1273 covid-19 vaccine: simulation agent based modeling study. bmj, 373.
Chopra, Ayush, et al. "flame: A Framework for Learning in Agent-based ModEls." Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems. 2024.