Lin Y.-TJiang J.-H.RKravets V.N.JIE-HONG JIANG2021-09-022021-09-02202010923152https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097964917&doi=10.1145%2f3400302.3415616&partnerID=40&md5=3c3c8872faddca1ed6179d9d4dae94e4https://scholars.lib.ntu.edu.tw/handle/123456789/580984Uniform sampling is an important method in statistics and has various applications in model counting, system verification, algorithm design, among others. Symbolic sampling in a Boolean space is a recently proposed technique that combines sampling and symbolic representation for effective Boolean reasoning. Under the framework of symbolic sampling, we propose a method to construct compact XOR circuits achieving uniform sampling in a given Boolean space. The method is further extended to biased sampling within a focused subspace of interest. Experimental results show the effectiveness of compact sampling circuit generation and its potential to facilitate Boolean reasoning. ? 2020 Association on Computer Machinery.Computer aided design; Sampling; Timing circuits; Algorithm design; Biased sampling; Boolean reasoning; Model Counting; Sampling circuits; Symbolic representation; System verifications; Uniform sampling; Importance samplingconference paper10.1145/3400302.34156162-s2.0-85097964917