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Dive into the second part of a comprehensive probabilistic programming tutorial led by Vikash Mansinghka from MIT. Explore advanced concepts and techniques in this field over the course of 1 hour and 11 minutes. Gain valuable insights from an expert in neurosymbolic programming for science as you deepen your understanding of probabilistic programming principles and applications.
Probabilistic Programming Tutorial - Part 2
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#Computer Science
#Machine Learning
#Probabilistic Programming
#Mathematics
#Statistics & Probability
#Statistical Modeling
#Bayesian Statistics
#Bayesian Inference
#Probability Theory
#Stochastic Processes
#Statistical Methods
#Markov Chain Monte Carlo
#Uncertainty Quantification
#Artificial Intelligence
#Generative AI
#Generative Models
#Computational Statistics
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