Hi there! I'm an AI research scientist. I'm currently studying topics related to program synthesis, probabilistic programming, and concept learning. In the past, I studied cognitive psychology as a PhD student and then postdoc at Stanford.

Manuscripts

• Practical optimal experiment design with probabilistic programs
  Ouyang, L.*, Tessler M.H.*, Ly D.*, & Goodman N. D
  
• Learning to learn by teaching: generating helpful examples facilitates learning from helpful examples
  Ouyang, L., MacPherson A., & Goodman N. D
  

Publications

• Support and influence analysis for visualizing posteriors of probabilistic programs
  Ouyang, L.
  POPL 2017 Probabilistic Programming Systems workshop
  
• Semantic coherence facilitates distributional learning
  Ouyang, L., Boroditsky, L., & Frank, M. C.
  Cognitive Science
  Code & data
• Fabular: Regression formulas as probabilistic programming
  Borgstrom, J. D., Gordon, A. D., Ouyang, L., Russio, C., Scibior A., & Szymczak, M. POPL 2016
• Semantic coherence facilitates distributional learning of word meanings
  Ouyang, L., Boroditsky, L., & Frank, M. C.
  CogSci 2012

Presentations

• Probabilistic programming tutorial
  Stuhlmüller, A., & Ouyang, L.
  Next.ML San Francisco 2015
• Transfer in human concept learning
  Ouyang, L. & Goodman, N. D.
  UAI 2012 Natural Intelligence workshop