Resources
Resources
Some books
- Web book probmods.org
- Principle of Neural Design (link)
- How The Mind Works (link)
- Information Theory, Inference, and Learning Algorithms (link to free pdf)
Tutorials and labs
Teaching
- Algorithms of the Mind (PSYC 261/561): This course introduces computational theories of psychological processes, with a pedagogical focus on perception and high-level cognition. Each week students learn about new computational methods grounded in neural and/or cognitive phenomena. Lectures introduce these topics conceptually; lab sections provide hands-on instruction with programming assignments and review of mathematical concepts. Lectures cover a range of computational methods across the fields of computational statistics, artificial intelligence, and machine learning including probabilistic programming, artificial neural networks, differentiable simulators, and sampling- and optimization-based inference methods. Students work through weekly lab sections, weekly reading responses, four homework assignments, in addition to a final paper or a computational modeling project.
- Statistics (PSYC 200): This course provides a practical introduction to statistical concepts and methods in psychology. The course will emphasize both conceptual understanding of statistical techniques and their appropriate application to relevant research questions in psychological research. Students will learn to critically evaluate statistical claims and learn approaches to problems of statistical prediction. This is not a math class. The focus is on developing quantitative reasoning and using statistics as a tool for evaluating data. There will be very little hand-written problem solving, but there will be abundant programming assignments. These assignments will focus on conceptual understanding of statistics and implementing statistical tests using a statistical computing language.
- Computational basis of seeing and thinking (PSYC 479/679): The goal of this seminar is to discuss the computational basis of seeing and thinking in the mind and brain. We will be especially concerned with this question of "how perception gets us to cognition": How is it that perception transforms raw, unstructured incoming sensory signals arising from our physical environments -- the light that bounces off surfaces and arrives at the retina, raw audio waves hitting the ears, or the vibro-tactile sensations felt at the fingertips when touching a surface -- into things like objects, scenes, events, and agents, into things that we can think about? We draw upon readings and classroom discussions to find out where the literature stands, including behavioral, neural, and computational studies, all in the context of searching for a mechanistic, functional account of seeing and thinking in the mind and brain.