Publikationen von S Wu

Wu, S.; Thalmann, M.; Schulz, E.: Two types of motifs enhance human recall and generalization of long sequences. Communications Psychology 3 (1), 3 (2025)

Wu, S.; Éltetö, N.; Dasgupta, I.; Schulz, E.: Chunking as a rational solution to the speed-accuracy trade-off in a serial reaction time task. Scientific Reports 13, 7680 (2023)

Wu, S.; Thalmann, M.; Schulz, E.: Learning abstractions from discrete sequences. In: 46th Annual Conference of the Cognitive Science Society (CogSci 2024). 46th Annual Conference of the Cognitive Science Society (CogSci 2024), Rotterdam, The Netherlands, 24. Juli 2024 - 27. Juli 2024. (2024)

Schreiber, A.; Wu, S.; Wu, C.; Indiveri, G.; Schulz, E.: Biologically-plausible hierarchical chunking on mixed-signal neuromorphic hardware. In: NeurIPS 2023 Workshop: Machine Learning with New Compute Paradigms. NeurIPS 2023 Workshop: Machine Learning with New Compute Paradigms, New Orleans, LA, USA, 16. Dezember 2023. (2023)

Wu, S.; Thalmann, M.; Schulz, E.: Projectional motifs facilitate sequence memorization and transfer. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.118, S. 1294 - 1296. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Wu, S.; Éltetö, N.; Dasgupta, I.; Schulz, E.: Learning Structure from the Ground up: Hierarchical Representation Learning by Chunking. In: Advances in Neural Information Processing Systems 35: 36th Conference on Neural Information Processing Systems (NeurIPS 2022), S. 36706 - 36721 (Hg. Koyejo, S.; Mohamed, S.). Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA, 28. November 2022 - 09. Dezember 2022. Curran, Red Hook, NY, USA (2023)

Wu, S.; Éltetö, N.; Dasgupta, I.; Schulz, E.: Learning Structure from the Ground up: Hierarchical Representation Learning by Chunking. In: Tenth International Conference on Learning Representations (ICLR 2022). Tenth International Conference on Learning Representations (ICLR 2022), 25. April 2022 - 29. April 2022. (2022)

Wu, S.; Yoerueten, M.; Wichmann, F.; Schulz, E.: Normalized Cuts Characterize Visual Recognition Difficulty of Amorphous Image Sub-parts. Computational and Systems Neuroscience Meeting (COSYNE 2024), Lisboa, Portugal (2024)

Wu, S.; Elteto, N.; Dasgupta, I.; Schulz, E.: Chunking as a rational solution to the speed-accuracy trade-off in a serial reaction time task. 43rd Annual Conference of the Cognitive Science Society (CogSci 2021), Wien, Austria (2021)

Binz, M.; Akata, E.; Bethge, M.; Brändle, F.; Callaway, F.; Coda-Forno, J.; Dayan, P.; Demircan, C.; Eckstein, M.; Éltetö, N. et al.; Griffiths, T.; Haridi, S.; Jagadish, A.; Ji-An; Kipnis, A.; Kumar, S.; Ludwig, T.; Mathony, M.; Mattar, M.; Modirshanechi, A.; Nath, S.; Peterson, J.; Rmus, M.; Russek, E.; Saanum, T.; Scharfenberg, N.; Schubert, J.; Schulze Buschoff, L.; Singhi, N.; Sui, X.; Thalmann, M.; Theis, F.; Truong, V.; Udandarao, V.; Voudouris, K.; Wilson, R.; Witte, K.; Wu, S.; Wulff, D.; Xiong, H.; Schulz, E.: Centaur: a foundation model of human cognition. (eingereicht)

Wu, S.; Thalmann, M.; Dayan, P.; Akata, Z.; Schulz, E.: Building, Reusing, and Generalizing Abstract Representations from Concrete Sequences. (eingereicht)

Wu, S.; Thalmann, M.; Schulz, E.: Motif Learning Facilitates Sequence Memorization and Generalization. (eingereicht)