Search results
Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability ...
Daphne Koller is part of Stanford Profiles, official site for faculty, postdocs, students and staff information (Expertise, Bio, Research, Publications, and more). The site facilitates research and collaboration in academic endeavors.
Daphne Koller. My main research focus is on using probabilistic models and machine learning to understand complex domains that involve large amounts of uncertainty. Within that topic, my work touches on many areas: representation, inference, learning, and decision making. We like to be driven by real-world problems, and therefore a lot of my ...
I am the Rajeev Motwani Professor in the Computer Science Department at Stanford University. I joined the department in September 1995. I also have a courtesy appointment in the Department of Pathology. I completed my PhD in 1993 at Stanford, and was a postdoctoral researcher at the Computer Science Division at UC Berkeley .
Sep 17, 2019 · Daphne Koller talks fast, punctuating her words with gesticular flourishes as she shows off lab equipment through big glass windows in her offices in South San Francisco. Along with a standard DNA ...
Jun 14, 2020 · Daphne Koller: The other model is a much easier startup effort in the sense that there’s all this data out there and you can go and collect it. You can do it with a team of purely data-science ...
Dec 5, 2011 · Daphne Koller Conversely, students with an aptitude for the topic can move ahead rapidly, avoiding boredom and disengagement. In short, everyone has access to a personalized experience that ...
