Probabilistic Effects. λθ
Benchmarking
Components of Interest in Monad-Bayes
How To Profile & Benchmark
Benchmark Log
Last updated on 13 Nov 2020
Published on 13 Nov 2020
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Activity
CPSing Monad Bayes
Inlining Monad Bayes
Papers
Asymptotic Improvement of Computations over Free Monads
Design and Implementation of Probabilistic Programming Language Anglican
Extensible Effects
Faster Coroutine Pipelines
Freer Monads, More Extensible Effects
Fusion for Free
Hakaru - Probabilistic Inference by Program Transformation
Hansei - Embedded Domain-Specific Languages for Probabilistic Programming (Oleg)
Introduction To Probabilistic Programming
Lightweight Implementations of Probabilistic Programming Languages
Research
Research Journal
Potential Approaches to Improving Monad Bayes
Probabilistic Language Design
Effects for Less
Literature Review
Case Study: Optimising Parsley
Optimising Core
Monad Bayes
Inference Transformers
Implementing HMM Simulation and Inference (using PMMH)
Documentation
How Conditioning and Scoring Works
Tooling
Cabal Projects
Benchmarking
Benchmark Log
How to Benchmark and Profile
Relevant Components of Monad Bayes for Profiling
Background
Embedding DSLs
Staging
SMC and PMMH
Handrolling Monad Transformer Stacks
MTL
MCMC and MH
Markov Chains
Hidden Markov Model
Delimited Continuations
Haskell Core
Inlining
Specialisation
Bayesian
Concurrency
Continuations
Coroutines