Publikationen von LM Schulze Buschoff

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.; Li, J.-A.; Kipnis, A.; Kumar, S.; Ludwig, T.; Mathony, M.; Mattar, M.; Modirshanechi, A.; Nath, S.; Peterson, J.; Rmus, M.; Russek, E.; Saanum, T.; 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.: A foundation model to predict and capture human cognition. Nature Epub ahead (2025)

Schulze Buschoff, L.; Akata, E.; Bethge, M.; Schulz, E.: Visual cognition in multimodal large language models. Nature Machine Intelligence 7, S. 96 - 106 (2025)

Schulze Buschoff, L.; Schulz, E.; Binz, M.: The Acquisition of Physical Knowledge in Generative Neural Networks. In: 40th International Conference on Machine Learning, S. 30321 - 30341 (Hg. Krause, A.; Brunskill, E.; Cho, K.; Engelhardt, B.; Sabato, S. et al.). Fortieth International Conference on Machine Learning (ICML 2023), Honolulu, HI,USA, 23. Juli 2023 - 29. Juli 2023. (2023)

Meding, K.; Schulze Buschoff, L.; Geirhos, R.; Wichmann, F.: ImageNet suffers from dichotomous data difficulty. In: NeurIPS 2021 Workshop on ImageNet: past, present, and future, S. 1 - 27. NeurIPS 2021 Workshop on ImageNet: past, present, and future, 13. Dezember 2021 - 14. Dezember 2021. (2021)

Meding, K.; Schulze Buschoff, L.; Geirhos, R.; Wichmann, F.: Trivial or impossible: dichotomous data difficulty masks model differences (on ImageNet and beyond). (eingereicht)

Schulze Buschoff, L.; Akata, E.; Bethge, M.; Schulz, E.: Have we built machines that think like people? (eingereicht)

Schulze Buschoff, L.; Schulz, E.; Binz, M.: Stochastic Gradient Descent Captures How Children Learn About Physics. (eingereicht)