E. Schulz

PGC1α Regulates the Endothelial Response to Fluid Shear Stress via Telomerase Reverse Transcriptase Control of Heme Oxygenase-1

This study identifies a PGC-1-TERT-HMOX1 axis that regulates endothelial response to laminar fluid shear stress, promoting alignment and stability.

Inference and search on graph-structured spaces

The paper develops a Bayesian model of function learning on graph-structured spaces and shows it better predicts human behavior in reward search tasks than alternative models.

Similarities and differences in spatial and non-spatial cognitive maps

This study investigates how spatial and conceptual reasoning share and differ in computational principles using a Bayesian model of generalization in multi-armed bandit tasks.

A theory of learning to infer

The paper proposes a theory explaining systematic deviations in human probabilistic inference by introducing a recognition model that adapts to query distribution.

Communicating compositional patterns

The paper investigates how people communicate structure through a game, finding that compositional patterns are described more effectively than non-compositional ones.

Finding structure in multi-armed bandits

This study investigates how humans use latent structure in multi-armed bandit tasks to guide exploration and learning, finding that participants leverage functional relationships and develop learning-to-learn strategies.

Searching for rewards like a child means less generalization and more directed exploration

This study compares how children and adults search for rewards, finding that children explore more but generalize less, with directed exploration playing a key role.

Exploring the space of human exploration using Entropy Mastermind

This study investigates how people adapt their query strategies in complex environments using Entropy Mastermind, finding that lower entropy environments lead to more efficient problem-solving.

Generalization as diffusion: human function learning on graphs

The paper tests a model of human function learning on graphs by having participants predict passenger volumes in a subway network, finding that diffusion-based generalization outperforms heuristic models.

Exploration in the wild

The paper analyzes customer behavior in an online food delivery service to understand exploratory strategies in real-world decision-making.

Generalization guides human exploration in vast decision spaces

This study investigates how humans navigate vast decision spaces using generalization, finding that Gaussian Process function learning with an optimistic Upper Confidence Bound strategy explains human search behavior.

Generalization and search in risky environments

The paper studies how people search for rewards in risky environments and finds that their behavior aligns with a Gaussian process function learning algorithm that prioritizes safety.

Compositional Inductive Biases in Function Learning

The paper shows humans prefer compositional structures in function learning, finding them more predictable and memorable than non-compositional ones.

Putting bandits into context: How function learning supports decision making

The paper investigates how participants learn and make decisions in uncertain environments using contextual multi-armed bandit tasks, finding that Gaussian process learning strategies are effective in various contexts.

Remembrance of Inferences Past

The paper shows humans use amortized inference in probabilistic reasoning, reusing summary statistics from previous queries to save cognitive resources.

Amortized Hypothesis Generation

The paper demonstrates that people use amortized inference strategies when answering related queries, caching summary statistics rather than raw samples.