연구
소프트웨어 엔지니어링에 머신러닝 방법 적용
← 연구소로 돌아가기
프로젝트
E. Bogomolov
Astminer
A. Lobanov, E. Bogomolov, Y. Golubev
Codeforces Tags Prediction
A. Birillo, M. Tigina, Y. Golubev
Hyperstyle
V. Tankov
Kotless
A. Birillo, Y. Golubev, M. Tigina, A. Vlasova
Lupa
V. Tankov, A. Birillo
Reflekt
E. Bogomolov, O. Petrova, M. Evtikheev
Large-scale pre-training of graph neural networks for ML4SE tasks
M. Evtikheev, E. Bogomolov
Evaluation of performance metrics for code generation models
Mikhail Evtikheev, Egor Bogomolov
Evaluation of existing optimization methods for neural networks
A. Eliseeva, E. Bogomolov
Completion of commit messages
E. Bogomolov
Per-project fine-tuning of neural models
E. Bogomolov
IRen
E. Bogomolov
Detecting and updating inconsistent code comments
E. Bogomolov, O. Petrova
Type inference in Python
D. Litvinov
Generation of SQL queries from natural language
S. Titov, Y. Golubev
Jupyter 노트북 대규모 분석
S. Titov
Jupyter 노트북의 코드 클론 분석
S. Titov, Y. Golubev
Non-linear Jupyter notebooks
S. Titov, Y. Golubev
Overcoming the Mental Set effect
S. Titov
Attention in programming
O. Smirnov
Code reachability study
A. Birillo, M. Tigina
Predicting static analyzer output with machine learning
A. Birillo, M. Tigina, A. Lobanov
Clustering MOOC submissions
O. Smirnov, V. Tankov
Paddle
A. Tuchina, V. Tankov
KInference
M. Tigina
Commit cleaner
M. Tigina
KotlinRMiner
보관된 프로젝트
