| Using large-scale experiments and machine learning to discover theories of human decision-making JC Peterson, DD Bourgin, M Agrawal, D Reichman, TL Griffiths Science 372 (6547), 1209-1214, 2021 | 177 | 2021 |
| The temporal dynamics of opportunity costs: A normative account of cognitive fatigue and boredom M Agrawal, MG Mattar, JD Cohen, ND Daw Psychological Review, 2021 | 68 | 2021 |
| Scaling up psychology via scientific regret minimization M Agrawal, JC Peterson, TL Griffiths Proceedings of the National Academy of Sciences 117 (16), 8825-8835, 2020 | 50 | 2020 |
| Predicting beta bursts from local field potentials to improve closed-loop DBS paradigms in Parkinson’s patients EM Moraud, G Tinkhauser, M Agrawal, P Brown, R Bogacz 2018 40th Annual International Conference of the IEEE Engineering in …, 2018 | 24 | 2018 |
| Pyglmnet: Python implementation of elastic-net regularized generalized linear models M Jas, T Achakulvisut, A Idrizović, D Acuna, M Antalek, V Marques, ... Journal of Open Source Software 5 (47), 2020 | 22 | 2020 |
| Using machine learning to guide cognitive modeling: A case study in moral reasoning M Agrawal, JC Peterson, TL Griffiths Proceedings of the 41st Annual Conference of the Cognitive Science Society., 2019 | 14 | 2019 |
| Stress, intertemporal choice, and mitigation behavior during the COVID-19 pandemic M Agrawal, JC Peterson, JD Cohen, TL Griffiths PsyArXiv, 2022 | 3 | 2022 |
| A computational model of unintentional mind wandering in focused attention meditation I Christian, M Agrawal Proceedings of the 44th Annual Conference of the Cognitive Science Society., 2022 | | 2022 |
| Maxim Consequentialism for Bounded Agents M Agrawal, D Danks | | |
Thomas L. GriffithsProfessor of Psychology and Computer Science, Princeton UniversityVerified email at princeton.edu
