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[LAFI'22] Rigorous Approximation of Posterior Inference for Probabilistic Programs
[OOPSLA] Approximate Computation with Outlier Detection in Topaz
[OOPSLA24] Exact Bayesian Inference for Loopy Probabilistic Programs Using Generating Functions
Effects as Capabilities: Effect Handlers and Lightweight Effect Polymorphism (OOPSLA'20)
[POPL'24] Inference of Probabilistic Programs with Moment-Matching Gaussian Mixtures
I Used Bayesian Inference to Predict Coin Tosses in Julia
Ragged Paged Attention: A High-Performance and Flexible LLM Inference Kernel for TPU
[VMCAI'24] Guaranteed inference for probabilistic programs: a parallelisable, small-step o...
[OOPSLA] Scrap your Boilerplate with Object Algebras
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Last Updated: September 21, 2026
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Summary
Programmable MCMC with Soundly Composed Guide Programs (Video, This is the poster presentation for the Jonathan Brachthäuser presents the underlying design decisions of the Effekt language at the youtube.com/watch?v=LUAi-mbQo0o&list=PLLlTVphLQsuPH-CZ-k-tzvXRHGhACOKtv ... We walk through the Week 1 binomial, one-parameter model implemented in a grid Jevin Jiang from Google introduces how to accelerate dynamic and mixed-batch LLM Talk Title: Scrap your Boilerplate with Object Algebras Presenter: Haoyuan Zhang More Info: ...
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