A means to quantify the ability to discern between signal and noise.
A model that applies the Ising model to explain coherence in human reasoning.
A method in Bayesian inference that samples from the posterior distribution.
Models that describe transitions between different states of matter or systems.
Models that describe how people integrate multiple cues to make judgments.
A computational model for simulating the interactions of agents to assess their effects on the system.
A framework that combines rational models with assumptions about cognitive limitations.
Reasoning and making decisions based on probabilities.
A model that explains decision making by finding a consistent assignment of values to variables.
A theoretical framework for understanding the mind as a network of simple units.
Models that explain how humans learn and abstract categories from examples.
Models that explain how humans categorize objects and concepts.
A model of decision making that incorporates both leakage and competition between accumulating evidence.
Graphical models that represent causal relationships between variables.
A type of catastrophe model that describes how small changes in conditions can lead to sudden shifts in behavior.
A mathematical model of ferromagnetism in statistical mechanics.
Models that explain how memory functions in the human brain.
Models that use statistical methods to describe and infer patterns in data.
Models that represent systems as networks of interconnected nodes.
A type of machine learning where an agent learns to make decisions by receiving rewards or penalties.
A cognitive model that describes decision making as a process of evidence accumulation.
Models that explain decision making through the accumulation of evidence over time.
A framework for modeling the change in variables over time using differential equations.
A model of categorization where objects are classified based on their similarity to specific examples.
A multivariate statistical analysis technique that is used to analyze structural relationships.
A method of approximate inference that leverages neural networks to perform rapid Bayesian inference.
