Cognitive maps are mental representations of spatial and conceptual relationships in an
environment, and are critical for flexible behavior. To form these abstract maps, the …

We present 3DP3, a framework for inverse graphics that uses inference in a structured generative
model of objects, scenes, and images. 3DP3 uses (i) voxel models to represent the 3D …

The enormous popularity of smartphones, their rich sensing capabilities, and the data they
have about their users have lead to millions of apps being developed and used. However, …

This paper introduces SMCP3, a method for automatically implementing custom sequential
Monte Carlo samplers for inference in probabilistic programs. Unlike particle filters and …

The ability to perceive and understand 3D scenes is crucial for many applications in
computer vision and robotics. Inverse graphics is an appealing approach to 3D scene …

To facilitate the development of new models to bridge the gap between machine and
human social intelligence, the recently proposed Baby Intuitions Benchmark (arXiv:2102.11938) …

Variable order sequence modeling is an important problem in artificial and natural intelligence.
While overcomplete Hidden Markov Models (HMMs), in theory, have the capacity to …

Probabilistic graphical models (PGMs) provide a compact representation of knowledge that
can be queried in a flexible way: after learning the parameters of a graphical model once, …

Sequence learning is a vital cognitive function and has been observed in numerous brain
areas. Discovering the algorithms underlying sequence learning has been a major endeavour …

Cognitive maps are mental representations of spatial and conceptual relationships in an
environment. These maps are critical for flexible behavior as they permit us to navigate …