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Decoding latent attention across cognitive models
Maher CM, Saez I, Radulescu A
(2025) Reinforcement Learning and Decision Making
Act-Now vs. Look-Ahead: a Dual-Beta framework of self-efficacy in reinforcement learning
Li J, Ho MK*, Radulescu A*
(2025) Reinforcement Learning and Decision Making
Linking neural representations to adaptive behavior with cognitive modeling
Maher CM, Qasim S, Nunez Martinez L, Radulescu A*, Saez I*
(2025) Re-Align Workshop, ICLR
Rewards transiently and automatically enhanced sustained attention
Trach JE, deBettencourt MT, Radulescu A, McDougle SD
(2024) Journal of Experimental Psychology: General
Unveiling the latent dynamics in social cognition with multi-agent inverse reinforcement learning
Chen Y, Radulescu A, Wu HZ
(2024) bioRxiv
Zhu J, Radulescu A, Bennett D
(2024) Affective Science
Dynamic self-efficacy as a computational mechanism of mania emergence
Li J, Radulescu A
(2024) Proceedings of the Annual Meeting of the Cognitive Science Society
Affect-congruent attention drives changes in reward expectations
Bennett D*, Radulescu A*, Zorowitz S, Felso V, & Niv Y
(2023) PLOS Computational Biology
Naturalistic reinforcement learning
Wise T, Emery KJ, Radulescu A
(2023) Trends in Cognitive Sciences
Modeling human eye movements during immersive visual search
Radulescu A*, van Opheusden B*, Callaway F, Griffiths TL, & Hillis JM
(2022) bioRxiv
Name that state: How language affects human reinforcement learning
Radulescu A, Vong WK, Gureckis TM
(2022) Proceedings of the Annual Meeting of the Cognitive Science Society
Radulescu A, Shin Y, Niv Y
(2021) Annual Review of Neuroscience
From heuristic to optimal models in naturalistic visual search
Radulescu A*, van Opheusden B*, Callaway F, Griffiths TL, Hillis JM
(2020) Bridging AI and Cognitive Science workshop, ICLR
On the convergent validity of risk sensitivity measures
Radulescu A, Holmes K, Niv Y
(2020) PsyArXiv
Daniel R, Radulescu A, Niv Y
(2020) Journal of Neuroscience
A particle filtering account of selective attention during learning
Radulescu A, Niv Y, Daw ND
(2019) Computational Cognitive Neuroscience
State representation in mental illness
Radulescu A, Niv Y
(2019) Current opinion in neurobiology
Holistic reinforcement learning: the role of structure and attention
Radulescu A, Niv Y, Ballard IC
(2019) Trends in Cognitive Sciences
Contrasting the effects of prospective attention and retrospective decay in representation learning
Davidson G*, Radulescu A*, Niv Y
(2019) Reinforcement Learning and Decision Making
Dynamic interaction between reinforcement learning and attention in multidimensional environments
Leong YC*, Radulescu A*, Daniel R, DeWoskin V, Niv Y
(2017) Neuron
Reward sensitive attention dynamics during human reinforcement learning
Radulescu A, Leong YC, Niv Y
(2017) Reinforcement Learning and Decision Making
Building on solid ground: establishing the stability of computational modeling parameters
Hitchcock P, Radulescu A, Niv Y, Sims C
(2017) Annual Convention for the Association for Behavioral and Cognitive Therapies
The effects of aging on the interaction between reinforcement learning and attention
Radulescu A, Daniel R, Niv Y
(2016) Psychology and Aging
DYT1 dystonia increases risk taking in humans
Arkadir D, Radulescu A, Lubarr N, Raymond D, Bressman SB, Mazzoni P, Niv Y
(2016) eLife
Reinforcement learning in multidimensional environments relies on attention mechanisms
Niv Y, Daniel R, Geana A, Gershman SJ, Leong Y, Radulescu A, Wilson RC
(2015) Journal of Neuroscience
Statistical computations underlying the dynamics of memory updating
Gershman SJ, Radulescu A, Norman KA, Niv Y
(2014) PLOS Computational Biology