activity
20172021
most citedExpected-Cost Analysis for Probabilistic Programs and Semantics-Level Adaption of Optional Stopping Theorems

2 citations · 5 across the 6 of their papers we have counts for

collaborators
Showing cs.PLShow all

14 papers · 1 filter

cs.PL2021

Automatic Amortized Resource Analysis with the Quantum Physicist's Method

David M Kahn, Jan Hoffmann

We present a novel method for working with the physicist's method of amortized resource analysis, which we call the quantum physicist's method. These principles allow for more prec…

cs.PL20211 cited

Sound Probabilistic Inference via Guide Types

Di Wang, Jan Hoffmann, Thomas Reps

Probabilistic programming languages aim to describe and automate Bayesian modeling and inference. Modern languages support programmable inference, which allows users to customize i…

cs.PL20212 cited

Expected-Cost Analysis for Probabilistic Programs and Semantics-Level Adaption of Optional Stopping Theorems

Di Wang, Jan Hoffmann, Thomas Reps

In this article, we present a semantics-level adaption of the Optional Stopping Theorem, sketch an expected-cost analysis as its application, and survey different variants of the O…

cs.PL20202 cited

Probabilistic Resource-Aware Session Types

Ankush Das, Di Wang, Jan Hoffmann

Session types guarantee that message-passing processes adhere to predefined communication protocols. Prior work on session types has focused on deterministic languages but many mes…

cs.PL2020

Typable Fragments of Polynomial Automatic Amortized Resource Analysis

Long Pham, Jan Hoffmann

Being a fully automated technique for resource analysis, automatic amortized resource analysis (AARA) can fail in returning worst-case cost bounds of programs, fundamentally due to…

cs.PL2020

Liquid Resource Types

Tristan Knoth, Di Wang, Adam Reynolds +2

This article presents liquid resource types, a technique for automatically verifying the resource consumption of functional programs. Existing resource analysis techniques trade au…