Preprint (29)

121.
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Heinrichs, H.; Spitschan, M.: Within-subjects ultra-short sleep-wake protocol for characterising circadian variations in retinal function. (submitted)
122.
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Mahler, L.; Steiglechner, J.; Wang, Q.; Scheffler, K.; Heule, R.: Flexible and Cost-Effective Deep Learning for Fast Multi-Parametric Relaxometry using Phase-Cycled bSSFP. (submitted)
123.
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West, D.; Glang, F.; Endres, J.; Leitão, D.; Zaiss, M.; Hajnal, J.; Malik, S.: MR sequence design using digital twins of non-idealized hardware. (submitted)
124.
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Young, T.; Kumar, V.; Saranathan, M.: Normative modeling of thalamic nuclear volumes. (submitted)
125.
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Alon, N.; Schulz, L.; Bell, V.; Moutoussis, M.; Dayan, P.; Barnby, J.: Overly deep hierarchical mentalizing produces paranoia: a new formal theory. (submitted)
126.
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Biller, A.; Fatima, N.; Hamberger, C.; Hainke, L.; Plankl, V.; Nadeem, A.; Kramer, A.; Hecht, M.; Spitschan, M.: The Ecology of Human Sleep (EcoSleep) Project: Protocol for a longitudinal cohort repeated-measurement-burst study to assess the relationship between sleep determinants and sleep outcomes under real-world conditions across time of year. (submitted)
127.
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Coda-Forno, J.; Binz, M.; Wang, J.; Schulz, E.: CogBench: a large language model walks into a psychology lab. (submitted)
128.
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Guidolin, C.; Udovicic, L.; Broszio, K.; Baeza Moyano, D.; Melero-Tur, S.; Cantarero-Garcia, G.; González-Lezcano, R.; Aerts, S.; Bolte, J.; Joosten-Ma, H. et al.; Nilsson Tengelin, M.; Stefani, O.; Didikoğlu, A.; Zauner, J.; Spitschan, M.: Protocol for a prospective, multi-centric, cross-sectional cohort study to assess personal light exposure. (submitted)
129.
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Jagadish, A.; Coda-Forno, J.; Thalmann, M.; Schulz, E.; Binz, M.: Ecologically rational meta-learned inference explains human category learning. (submitted)
130.
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Schubert, J.; Jagadish, A.; Binz, M.; Schulz, E.: In-context learning agents are asymmetric belief updaters. (submitted)
131.
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Shen, T.; Dayan, P.: Risking your Tail: Modeling Individual Differences in Risk-sensitive Exploration using Conditional Value at Risk and Bayes Adaptive Markov Decision Processes. (submitted)
132.
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Wu, C.; Meder, B.; Schulz, E.: Unifying principles of generalization: past, present, and future. (submitted)
133.
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Basgol, H.; Dayan, P.; Franz, V.: Violation of Auditory Regularities is Reflected in Pupil Dynamics. (submitted)
134.
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Choi, S.; Hike, D.; Pohmann, R.; Avdievich, N.; Gomez Cid, L.; Man, W.; Scheffler, K.; Yu, X.: Alpha-180 spin-echo based line-scanning method for high resolution laminar-specific fMRI. (submitted)
135.
Preprint
Fardet, T.; Giannakakis, E.; Paulun, K.; Levina, A.: Revising clustering and small-worldness in brain networks. (submitted)
136.
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Hedrich, N.; Schulz, E.; Hall-McMaster, S.; Schuck, N.: An inductive bias for slowly changing features in human reinforcement learning. (submitted)
137.
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Shen, T.; Dayan, P.: Risking your Tail: Curiosity, Danger and Exploration. (submitted)
138.
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Wu, C.; Deffner, D.; Kahl, B.; Meder, B.; Ho, M.; Kurvers, R.: Visual-spatial dynamics drive adaptive social learning in immersive environments. (submitted)
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