Research

Context

Determining whether two stimuli should evoke the same (stable) response or lead to a transition requires inferring how stimulus properties generalize relative to the context. Here, we focus on how the context in which an item is embedded helps or hinders its processing. Successful context processing makes us skilled in scene and object perception, while overgeneralization leads to disorders like phobias.

New project-related publications
Cheeseman, J. R., Fleming, R., & Schmidt, F. (2021).
Scale Ambiguities in Material Recognition.
PsyArXiv Preprints
McKay, C., Wijeakumar, S., Rafetseder, E., & Shing, Y. L. (2021).
Disentangling Age and Schooling Effects on Inhibitory Control Development: An fNIRS Investigation.
bioRxiv
Meibodi, N., Abbasi, H., Schubö, A., & Endres, D. M. (2021).
A model of selection history in visual attention.
In Proceedings of the Annual Meeting of the Cognitive Science Society 43(43), 707-713.
Preißler, L., Jovanovic, B., Munzert, J., Schmidt, F., Fleming, R.W., & Schwarzer, G. (2021).
Effects of visual and visual-haptic perception of material rigidity on reaching and grasping in the course of development
Acta Psychologica, 221, November, 103457
Storrs, K. R., Anderson, B. L., & Fleming, R. W. (2021).
Unsupervised learning predicts human perception and misperception of gloss.
Nature Human Behaviour, 1-16.
DOI
Thoma, N., Yu, Z., Ventola, F., & Kersting, K. (2021).
RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting.
Proceedings of the 4th Workshop on Tractable Probabilistic Modeling (TPM 2021).
Ventola, F., Dhami, D. S., & Kersting, K. (2021).
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits.
Proceedings of the 30th International Conference on Inductive Logic Programming (ILP).
Yu, Z., Dhami, D. S., & Kersting, K. (2021).
Sum-Product-Attention Networks: Leveraging Self-Attention in Probabilistic Circuits.
arXiv preprint
Yu, Z., Ventola, F. G., & Kersting, K. (2021).
Whittle networks: A deep likelihood model for time series.
International Conference on Machine Learning (PMLR), 12177-12186.
Yu, Z., Zhu, M., Trapp, M., Skryagin, A., & Kersting, K. (2021).
Leveraging Probabilistic Circuits for Nonparametric Multi-Output Regression.
Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021).
Zečević, M., Dhami, D. S., Rothkopf, C. A., & Kersting, K. (2021).
Structural Causal Interpretation Theorem.
arXiv preprint