Ulrich Schaechtle
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View article: GenSQL: A Probabilistic Programming System for Querying Generative Models of Database Tables
GenSQL: A Probabilistic Programming System for Querying Generative Models of Database Tables Open
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 for querying probabilistic models, GenSQL enables complex Ba…
View article: Elements of a stochastic 3D prediction engine in larval zebrafish prey capture
Elements of a stochastic 3D prediction engine in larval zebrafish prey capture Open
The computational principles underlying predictive capabilities in animals are poorly understood. Here, we wondered whether predictive models mediating prey capture could be reduced to a simple set of sensorimotor rules performed by a prim…
View article: Elements of a stochastic 3D prediction engine in larval zebrafish prey capture
Elements of a stochastic 3D prediction engine in larval zebrafish prey capture Open
Many predatory animals rely on accurate sensory perception, predictive models, and precise pursuits to catch moving prey. Larval zebrafish intercept paramecia during their hunting behavior, but the precise trajectories of their prey have n…
View article: Gaussian Process Structure Learning via Probabilistic Inverse Compilation
Gaussian Process Structure Learning via Probabilistic Inverse Compilation Open
There is a widespread need for techniques that can learn interpretable models from data. Recent work by Duvenaud et al. (2013) and Lloyd et al. (2014) showed that it is possible to use Gaussian Processes (GPs) to discover symbolic structur…
View article: Time Series Structure Discovery via Probabilistic Program Synthesis
Time Series Structure Discovery via Probabilistic Program Synthesis Open
There is a widespread need for techniques that can discover structure from time series data. Recently introduced techniques such as Automatic Bayesian Covariance Discovery (ABCD) provide a way to find structure within a single time series …
View article: Probabilistic Programming with Gaussian Process Memoization
Probabilistic Programming with Gaussian Process Memoization Open
Gaussian Processes (GPs) are widely used tools in statistics, machine learning, robotics, computer vision, and scientific computation. However, despite their popularity, they can be difficult to apply; all but the simplest classification o…