A combined passive and active musculoskeletal model study to estimate L4-L5 load sharing F Azari, N Arjmand, A Shirazi-Adl, T Rahimi-Moghaddam Journal of biomechanics 70, 157-165, 2018 | 53 | 2018 |
Boosting Theory-of-Mind Performance in Large Language Models via Prompting SR Moghaddam, CJ Honey arXiv preprint arXiv:2304.11490v3, 2023 | 39 | 2023 |
Brain-inspired architectures for efficient and meaningful learning from temporally smooth data S Rahimi Moghaddam, F Bu, CJ Honey Computational and Systems Neuroscience (COSYNE), 2021 | | 2021 |
Consequences of Slow Neural Dynamics for Incremental Learning S Rahimi Moghaddam, F Bu, CJ Honey arXiv e-prints, arXiv: 2012.06694, 2020 | | 2020 |
Learning from temporally clustered information in artificial and biological neural networks S Rahimi Moghaddam, CJ Honey Context and Episodic Memory Symposium, 2020 | | 2020 |
Learning from smooth information S Rahimi Moghaddam, F Bu, CJ Honey From Neuroscience to Artificially Intelligent Systems, 2020 | | 2020 |
Effects of Temporal Clustering on Learning in Neural Networks S Rahimi Moghaddam, F Bu, CJ Honey Society for Neuroscience, 2019 | | 2019 |
Modeling of Preference Reversal in a Temptation Task S Rahimi Moghaddam, J Hwang, EE Emeric, V Stuphorn Society for Neuroeconomics, 2017 | | 2017 |
A detailed finite element modeling of the L4–L5 lumbar motion segment S Rahimi Moghaddam Sharif University of Technology, 2014 | | 2014 |