Publikationen von SF Bucher

Bucher, S.; Brandenburger, A.: Divisive normalization is an efficient code for multivariate Pareto-distributed environments. Proceedings of the National Academy of Sciences of the United States of America 119 (40), e2120581119 (2022)

Bucher, S.; Dayan, P.: Cognitive Information Filters: Algorithmic Choice Architecture for Boundedly Rational Consumers. In: NeurIPS 2023 workshop: Information-Theoretic Principles in Cognitive Systems: InfoCog@NeurIPS2023. NeurIPS 2023 workshop: Information-Theoretic Principles in Cognitive Systems: InfoCog@NeurIPS2023, New Orleans, LA, USA, 15. Dezember 2023. (2023)

Kurtz-David, V.; Alladi, V.; Bucher, S.; Brandenburger, A.; Louie, K.; Glimcher, P.; Tymula, A.: Choosers Adapt Value Coding to the Environment, But Do Not Attain Efficiency. 45th Annual Meeting of the Cognitive Science Society (CogSci 2023), Sydney, Australia, 26. Juli 2023 - 29. Juli 2023. Proceedings of the Annual Meeting of the Cognitive Science Society 45, S. 2237 - 2244 (2023)

Kurtz David, V.; Alladi, V.; Sinha, S.; Bucher, S.; Brandenburger, A.; Louie, K.; Dewan, A.; Glimcher, P.; Tymula, A.: Inefficient Divisive Normalization: Human Choosers Employ Divisive Normalization Even When They Should Not. In 52nd Annual Meeting of the Society for Neuroscience (Neuroscience 2023), NANO58.13, S. 544. 52nd Annual Meeting of the Society for Neuroscience (Neuroscience 2023), Washington, DC, USA, 11. November 2023 - 15. November 2023. (2023)

Bucher, S.; Brandenburger, A.: In what environments is divisive normalization an efficient computation? In 18th Annual Meeting of the Society for NeuroEconomics (vSNE 2020), S. 18. 18th Annual Meeting of the Society for NeuroEconomics (vSNE 2020), 07. Oktober 2020 - 09. Oktober 2020. (2020)

Bucher, S.; Yan, Z.-Y.; Shen, B.; Dayan, P.; Glimcher, P.: Reward Prediction Updates: Tracking Changes in Reward Expectations. Annual Meeting of the Society of NeuroEconomics (SNE 2024), Cascais, Portugal (2024)

Bucher, S.; Dayan, P.: Algorithmic Choice Architecture for Boundedly Rational Consumers. 10th Annual Conference on Digital Experimentation (CODE@MIT 2023), Cambridge, MA, USA (2023)

Bucher, S.; Dayan, P.: Dopamine-Revealed Preference and Beliefs over Resolving Uncertainty. Annual Meeting of the Society for NeuroEconomics (SNE 2022), Arlington, VA, USA (2022)

Bucher, S.; Yan, Z.-Y.; Glimcher, P.; Dayan, P.: Neurally Revealed Preference and Beliefs over Resolving Uncertainty. Annual Meeting of the Society for NeuroEconomics (SNE 2023), Vancouver, BC, Canada (2022)

Kurtz-David, V.; Alladi, V.; Bucher, S.; Louie, K.; Brandenburger, A.; Dewan, A.; Glimcher, P.; Tymula, A.: Choosing Well: Testing the Efficiency of Neural Value Coding. Annual Meeting of the Society for NeuroEconomics (SNE 2022), Arlington, VA, USA (2022)

Bucher, S.; Brandenburger, A.: Divisive normalization is an efficient code for multivariate Pareto-distributed environments. 50th Annual Meeting of the Society for Neuroscience (Neuroscience 2021) (2021)

Bucher, S.; Glimcher, P.: Late integration of prior belief in drift-diffusion models. 19th Annual Meeting of the Society for NeuroEconomics (vSNE 2021) (2021)

Bucher, S.; Glimcher, P.: Testing the DDM: A behavioral Experiment to measure evidence accumulation during decision making. 17th Annual Meeting of the Society for NeuroEconomics (SNE 2019), Dublin, Ireland (2019)