Vladimir Ulyantsev
Vladimir Ulyantsev
ITMO University
Verified email at - Homepage
Cited by
Cited by
Assessment of k-mer spectrum applicability for metagenomic dissimilarity analysis
VB Dubinkina, DS Ischenko, VI Ulyantsev, AV Tyakht, DG Alexeev
BMC bioinformatics 17, 1-11, 2016
MoG-VQE: Multiobjective genetic variational quantum eigensolver
D Chivilikhin, A Samarin, V Ulyantsev, I Iorsh, AR Oganov, O Kyriienko
arXiv preprint arXiv:2007.04424, 2020
Extended finite-state machine induction using SAT-solver
VI Ulyantsev, FN Tsarev
IFAC Proceedings Volumes 45 (6), 236-241, 2012
MetaFast: fast reference-free graph-based comparison of shotgun metagenomic data
VI Ulyantsev, SV Kazakov, VB Dubinkina, AV Tyakht, DG Alexeev
Bioinformatics 32 (18), 2760-2767, 2016
GADMA: Genetic algorithm for inferring demographic history of multiple populations from allele frequency spectrum data
E Noskova, V Ulyantsev, KP Koepfli, SJ O’Brien, P Dobrynin
GigaScience 9 (3), giaa005, 2020
BFS-based symmetry breaking predicates for DFA identification
V Ulyantsev, I Zakirzyanov, A Shalyto
Language and Automata Theory and Applications: 9th International Conference …, 2015
Genome-wide sequence analyses of ethnic populations across Russia
DV Zhernakova, V Brukhin, S Malov, TK Oleksyk, KP Koepfli, A Zhuk, ...
Genomics 112 (1), 442-458, 2020
MetaCherchant: analyzing genomic context of antibiotic resistance genes in gut microbiota
EI Olekhnovich, AT Vasilyev, VI Ulyantsev, ES Kostryukova, AV Tyakht
Bioinformatics 34 (3), 434-444, 2018
Exact finite-state machine identification from scenarios and temporal properties
V Ulyantsev, I Buzhinsky, A Shalyto
International Journal on Software Tools for Technology Transfer 20 (1), 35-55, 2018
MuACOsm: a new mutation-based ant colony optimization algorithm for learning finite-state machines
D Chivilikhin, V Ulyantsev
Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013
Learning finite-state machines with ant colony optimization
D Chivilikhin, V Ulyantsev
International Conference on Swarm Intelligence, 268-275, 2012
Evolutionary computation techniques for constructing SAT-based attacks in algebraic cryptanalysis
A Pavlenko, A Semenov, V Ulyantsev
Applications of Evolutionary Computation: 22nd International Conference …, 2019
Efficient symmetry breaking for SAT-based minimum DFA inference
I Zakirzyanov, A Morgado, A Ignatiev, V Ulyantsev, J Marques-Silva
Language and Automata Theory and Applications: 13th International Conference …, 2019
Finding all minimum-size DFA consistent with given examples: SAT-based approach
I Zakirzyanov, A Shalyto, V Ulyantsev
Software Engineering and Formal Methods: SEFM 2017 Collocated Workshops …, 2018
Applying reinforcement learning and supervised learning techniques to play hearthstone
I Kachalsky, I Zakirzyanov, V Ulyantsev
2017 16th IEEE International Conference on Machine Learning and Applications …, 2017
Hi-C metagenomics in the ICU: exploring clinically relevant features of gut microbiome in chronically critically ill patients
V Ivanova, E Chernevskaya, P Vasiluev, A Ivanov, I Tolstoganov, ...
Frontiers in microbiology 12, 770323, 2022
Smart contract design meets state machine synthesis: Case studies
D Suvorov, V Ulyantsev
arXiv preprint arXiv:1906.02906, 2019
Machine learning of phase transitions in nonlinear polariton lattices
D Zvyagintseva, H Sigurdsson, VK Kozin, I Iorsh, IA Shelykh, V Ulyantsev, ...
Communications Physics 5 (1), 8, 2022
Combining exact and metaheuristic techniques for learning extended finite-state machines from test scenarios and temporal properties
D Chivilikhin, V Ulyantsev, A Shalyto
2014 13th International Conference on Machine Learning and Applications, 350-355, 2014
Evolutionary approach to coverage testing of IEC 61499 function block applications
I Buzhinsky, V Ulyantsev, J Veijalainen, V Vyatkin
2015 IEEE 13th International Conference on Industrial Informatics (INDIN …, 2015
The system can't perform the operation now. Try again later.
Articles 1–20