Zoubin Ghahramani: "Probabilistic Machine Learning: From theory to industrial impact"
Комментарии отсутствуют
Информация о видео
Другие видео канала
Ulrich Schaechtle: Automated data modeling for science via Bayesian synthesis
Sarah Chasins: "Data-Driven Synthesis of Full Probabilistic Programs"
Yordan Zaykov: "Probabilistic programming in production with Infer.NET"
Yura Perov: "MultiVerse: Causal Reasoning in Probabilistic Programming using Importance Sampling"
Chung-Chieh Shan: "Calculating distributions"
Hugo Paquet: "Densities of almost-surely terminating probabilistic programs are differentiable..."
Jan Kudlicka: Probabilistic Programming for birth-death models of evolution...
Steven Holzen
Robert Osazuwa Ness: "Towards causal inference with latent variable models and programs"
Adam Scibior: "Denotational account of approximate Bayesian inference"
Dave Blei: "Black Box Variational Inference"
Iris Seaman: "Nested reasoning about autonomous agents using probabilistic programs"
Daniel Ritchie: "Learning Neurosymbolic 3D Models"
Kinjal Shah: Bean Machine
Maria Gorinova: "Efficient inference with discrete parameters in Stan"
Avi Bryant
Jean-Baptiste Tristan: "Compilation of Probabilistic Programs"
Frank Wood: "Inference Compilation"
Ekansh Sharma
Panel: Probabilistic Programming in the Field - Bayesian Data Modeling
Feras Saad: "Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling"