I'm an AI researcher studying how people and computers can work together more effectively. I'm primarily interested in program synthesis, probabilistic programming, and concept learning. In the past, I studied cognitive psychology as a PhD student and then postdoc at Stanford.
Publications
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webppl-oed: A practical optimal experiment design system
Ouyang, L., Tessler, M.H., Ly, D., & Goodman, N. D.
CogSci 2018
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Pedagogical learning
Ouyang, L. & Frank, M.C.
NIPS 2017 Teaching Machines workshop
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Support and influence analysis for visualizing posteriors of probabilistic programs
Ouyang, L.
POPL 2017 Probabilistic Programming Systems workshop
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Semantic coherence facilitates distributional learning
Ouyang, L., Boroditsky, L., & Frank, M. C.
Cognitive Science
Code & data
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Fabular: Regression formulas as probabilistic programming
Borgstrom, J. D., Gordon, A. D., Ouyang, L., Russio, C., Scibior A., & Szymczak, M.
POPL 2016
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Semantic coherence facilitates distributional learning of word meanings
Ouyang, L., Boroditsky, L., & Frank, M. C.
CogSci 2012
Presentations
Manuscripts