Gradient estimation of probabilistic programs reduces soundly to probabilistic inference after programmable coupling and factorization, enabling new low-variance estimators that beat baselines.
In: Foster, J.S., Grossman, D
5 Pith papers cite this work. Polarity classification is still indexing.
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Develops compositional incrementalization of density functions for probabilistic programs to accelerate Monte Carlo inference algorithms.
Kofola implements a modular SCC-based complementation framework for Büchi automata plus a new on-the-fly emptiness check, showing competitive or superior performance on practical benchmarks.
HELIX is an end-to-end verified code generator from mathematical formulations of cyber-physical systems to LLVM IR, using Coq, algebraic transformations, term rewriting, and sparse vector abstractions.
Data-access cost scales as N to the 1/4 in an abstract memory hierarchy for a class of applications.
citing papers explorer
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GradInf: Gradient Estimation as Probabilistic Inference
Gradient estimation of probabilistic programs reduces soundly to probabilistic inference after programmable coupling and factorization, enabling new low-variance estimators that beat baselines.
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Incremental Computation for Efficient Programmable Inference in Probabilistic Programs
Develops compositional incrementalization of density functions for probabilistic programs to accelerate Monte Carlo inference algorithms.
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Kofola 1.0: A Modular Approach to {\omega}-Regular Complementation and Inclusion Checking (Technical Report)
Kofola implements a modular SCC-based complementation framework for Büchi automata plus a new on-the-fly emptiness check, showing competitive or superior performance on practical benchmarks.
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HELIX: Verified compilation of cyber-physical control systems to LLVM IR
HELIX is an end-to-end verified code generator from mathematical formulations of cyber-physical systems to LLVM IR, using Coq, algebraic transformations, term rewriting, and sparse vector abstractions.
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The Fourth-Root Complexity of Data Movement
Data-access cost scales as N to the 1/4 in an abstract memory hierarchy for a class of applications.