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Constrained Sampling and Counting: Universal Hashing Meets SAT Solving

Constrained Sampling and Counting: Universal Hashing Meets SAT Solving

21 December 2015
Kuldeep S. Meel
Moshe Y. Vardi
Supratik Chakraborty
Daniel J. Fremont
Sanjit A. Seshia
Dror Fried
A. Ivrii
S. Malik
ArXiv (abs)PDFHTML

Papers citing "Constrained Sampling and Counting: Universal Hashing Meets SAT Solving"

16 / 16 papers shown
Title
Systematic Parameter Decision in Approximate Model Counting
Systematic Parameter Decision in Approximate Model Counting
Jinping Lei
Toru Takisaka
Junqiang Peng
Mingyu Xiao
106
0
0
08 Apr 2025
TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation
TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation
Lin Sun
Guangxiang Zhao
Xiaoqi Jian
Yuhan Wu
Weihong Lin
...
Junting Zhou
Wenrui Liu
Tengjiao Wang
Tong Yang
Xiangzheng Zhang
ALM
53
0
0
06 Mar 2025
Softened Symbol Grounding for Neuro-symbolic Systems
Softened Symbol Grounding for Neuro-symbolic Systems
Zenan Li
Yuan Yao
Taolue Chen
Jingwei Xu
Chun Cao
Xiaoxing Ma
Jian Lu
NAI
65
14
0
01 Mar 2024
Rounding Meets Approximate Model Counting
Rounding Meets Approximate Model Counting
Jiong Yang
Kuldeep S. Meel
46
7
0
16 May 2023
Data assimilation with agent-based models using Markov chain sampling
Data assimilation with agent-based models using Markov chain sampling
Daniel Tang
N. Malleson
45
3
0
03 May 2022
Exploiting complex pattern features for interactive pattern mining
Exploiting complex pattern features for interactive pattern mining
Arnold Hien
S. Loudni
Noureddine Aribi
Abdelkader Ouali
Albrecht Zimmermann
8
0
0
08 Apr 2022
Projected Model Counting: Beyond Independent Support
Projected Model Counting: Beyond Independent Support
Jiong Yang
Supratik Chakraborty
Kuldeep S. Meel
45
4
0
18 Oct 2021
Sparse Hashing for Scalable Approximate Model Counting: Theory and
  Practice
Sparse Hashing for Scalable Approximate Model Counting: Theory and Practice
Kuldeep S. Meel
S. Akshay
43
27
0
30 Apr 2020
Quantitative Verification of Neural Networks And its Security
  Applications
Quantitative Verification of Neural Networks And its Security Applications
Teodora Baluta
Shiqi Shen
Shweta Shinde
Kuldeep S. Meel
P. Saxena
AAML
89
105
0
25 Jun 2019
Weight Learning in a Probabilistic Extension of Answer Set Programs
Weight Learning in a Probabilistic Extension of Answer Set Programs
Joohyung Lee
Yi Wang
120
14
0
14 Aug 2018
Constrained Counting and Sampling: Bridging the Gap between Theory and
  Practice
Constrained Counting and Sampling: Bridging the Gap between Theory and Practice
Kuldeep S. Meel
34
23
0
06 Jun 2018
A New Probabilistic Algorithm for Approximate Model Counting
A New Probabilistic Algorithm for Approximate Model Counting
Cunjing Ge
Feifei Ma
Tian Liu
Jian Zhang
TPM
35
4
0
13 Jun 2017
Learning what matters - Sampling interesting patterns
Learning what matters - Sampling interesting patterns
V. Dzyuba
M. Leeuwen
57
12
0
07 Feb 2017
Computing Scores of Forwarding Schemes in Switched Networks with
  Probabilistic Faults
Computing Scores of Forwarding Schemes in Switched Networks with Probabilistic Faults
Guy Avni
Shubham Goel
T. Henzinger
G. Rodríguez-Navas
17
3
0
12 Jan 2017
Flexible constrained sampling with guarantees for pattern mining
Flexible constrained sampling with guarantees for pattern mining
V. Dzyuba
Matthijs van Leeuwen
Luc de Raedt
84
37
0
28 Oct 2016
Towards Verified Artificial Intelligence
Towards Verified Artificial Intelligence
Sanjit A. Seshia
Dorsa Sadigh
S. Shankar Sastry
113
203
0
27 Jun 2016
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