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Probabilistic Programming

Explore probabilistic programming concepts, from intuitive physics to computational theory of mind, with hands-on practice in web-based probabilistic programming languages.
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Probabilistic Programming in Python - Conf42 Python 2024
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Explore Bayesian statistics, probabilistic modeling, and MCMC in Python. Learn key concepts and practical applications through demonstrations and workflow explanations.
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Probabilistic Programming Tutorial - Part 1

Explore probabilistic programming fundamentals and applications with MIT expert Vikash Mansinghka in this comprehensive tutorial.
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The Hamiltonian Monte Carlo Revolution Is Open Source - Probabilistic Programming with PyMC3
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Explore Bayesian statistical computation and Hamiltonian Monte Carlo algorithms using PyMC3, an open-source probabilistic programming package. Learn to apply these advanced techniques to complex models in Python.
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ACM SIGPLAN
Probabilistic Programming with Programmable Variational Inference

Explore a modular approach to variational inference in probabilistic programming, enhancing expressiveness and enabling user-defined objectives with systematic gradient estimation transformations.
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Probabilistic Programming with Stochastic Probabilities

Explore a novel approach to probabilistic programming languages using stochastic probability estimation, enabling unrestricted stochastic control flow and programmable inference with custom proposals.
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ACM SIGPLAN
Bayesian Inference Using Probabilistic Programming

Explore Bayesian inference techniques and probabilistic programming concepts with expert insights from Hong Ge at LAFI'24.
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An Intrinsically-typed Probabilistic Programming Language in Coq - Extended Abstract

Explore formalization of intrinsically-typed probabilistic programming language in Coq, focusing on syntax, evaluation, and formal verification applications.
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Scaling Decision-Theoretic Probabilistic Programming Through Factorization

Explore dappl, a new probabilistic programming language for decision-making, offering scalable MEU reasoning and expressive modeling of complex real-world tasks.
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Probabilistic Programming Interfaces for Random Graphs: Markov Categories, Graphons, and Nominal Sets - POPL 2024

Explore semantic models of probabilistic programming languages over graphs, connecting graphons to equational theories through Markov categories, measure-theoretic probability, and nominal sets.
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Computational Genomics Summer Institute CGSI
Using the Pyro Probabilistic Programming Language for Statistical Genomics - CGSI 2024

Explore Pyro probabilistic programming for statistical genomics. Learn to model RNA splicing and implement isoform-specific knockdown using advanced computational techniques.
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Probabilistic AI School
Probabilistic Modeling and Programming Tutorial - Lecture 1

Explore probabilistic modeling and programming techniques with expert guidance, enhancing your AI and machine learning skills through hands-on tutorials and practical examples.
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Neurosymbolic Programming for Science
Probabilistic Programming Tutorial - Part 2

Explore advanced concepts in probabilistic programming, focusing on practical applications and techniques for scientific computing and data analysis.
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Topos Institute
Semantics for Reactive Probabilistic Programming

Delve into probabilistic synchronous languages and their semantics, exploring density-based interpretations, co-iterative execution, and relational frameworks for program equivalence verification.
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A New Proof Rule for Almost-Sure Termination in Probabilistic Programming

Discover a novel proof rule for demonstrating almost-sure termination in probabilistic programs, focusing on innovative variant functions and handling programs with demonic non-determinism.
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