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20172023
most citedSparse Hashing for Scalable Approximate Model Counting: Theory and Practice

5 citations · 7 across the 6 of their papers we have counts for

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8 papers · 1 filter

cs.LO2023

MDPs as Distribution Transformers: Affine Invariant Synthesis for Safety Objectives

S. Akshay, Krishnendu Chatterjee, Tobias Meggendorfer +1

Markov decision processes can be viewed as transformers of probability distributions. While this view is useful from a practical standpoint to reason about trajectories of distribu…

cs.LO2021

A Normal Form Characterization for Efficient Boolean Skolem Function Synthesis

Preey Shah, Aman Bansal, S. Akshay +1

Boolean Skolem function synthesis concerns synthesizing outputs as Boolean functions of inputs such that a relational specification between inputs and outputs is satisfied. This pr…

cs.LO2019

Knowledge Compilation for Boolean Functional Synthesis

S. Akshay, Jatin Arora, Supratik Chakraborty +3

Given a Boolean formula F(X,Y), where X is a vector of outputs and Y is a vector of inputs, the Boolean functional synthesis problem requires us to compute a Skolem function vector…

cs.LO20191 cited

Timed Systems through the Lens of Logic

S. Akshay, Paul Gastin, Vincent Juge +1

In this paper, we analyze timed systems with data structures, using a rich interplay of logic and properties of graphs. We start by describing behaviors of timed systems using grap…

cs.LO2018

What's hard about Boolean Functional Synthesis

S. Akshay, Supratik Chakraborty, Shubham Goel +2

Given a relational specification between Boolean inputs and outputs, the goal of Boolean functional synthesis is to synthesize each output as a function of the inputs such that the…

cs.LO2018

Distribution-based objectives for Markov Decision Processes

S. Akshay, Blaise Genest, Nikhil Vyas

We consider distribution-based objectives for Markov Decision Processes (MDP). This class of objectives gives rise to an interesting trade-off between full and partial information.…