490 citations · 1k across the 74 of their papers we have counts for
8 papers · 1 filter
Understanding Epistemic Language with a Language-augmented Bayesian Theory of Mind
Lance Ying, Tan Zhi-Xuan, Lionel Wong +2
How do people understand and evaluate claims about others' beliefs, even though these beliefs cannot be directly observed? In this paper, we introduce a cognitive model of epistemi…
Infinite Ends from Finite Samples: Open-Ended Goal Inference as Top-Down Bayesian Filtering of Bottom-Up Proposals
Tan Zhi-Xuan, Gloria Kang, Vikash Mansinghka +1
The space of human goals is tremendously vast; and yet, from just a few moments of watching a scene or reading a story, we seem to spontaneously infer a range of plausible motivati…
Building Machines that Learn and Think with People
Katherine M. Collins, Ilia Sucholutsky, Umang Bhatt +10
What do we want from machine intelligence? We envision machines that are not just tools for thought, but partners in thought: reasonable, insightful, knowledgeable, reliable, and t…
Probabilistic Programming with Programmable Variational Inference
McCoy R. Becker, Alexander K. Lew, Xiaoyan Wang +4
Compared to the wide array of advanced Monte Carlo methods supported by modern probabilistic programming languages (PPLs), PPL support for variational inference (VI) is less develo…
GenSQL: A Probabilistic Programming System for Querying Generative Models of Database Tables
Mathieu Huot, Matin Ghavami, Alexander K. Lew +6
This article presents GenSQL, a probabilistic programming system for querying probabilistic generative models of database tables. By augmenting SQL with only a few key primitives f…
Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness
Aidan Curtis, George Matheos, Nishad Gothoskar +4
Integrated task and motion planning (TAMP) has proven to be a valuable approach to generalizable long-horizon robotic manipulation and navigation problems. However, the typical TAM…