Traffic Flow Forecasting Algorithm Based on Combination of Adaptive Elementary Predictors. - Anton Agafonov; Vladislav V. Myasnikov (AIST, 2015)

An Adaptive Algorithm for Public Transport Arrival Time Prediction Based on Hierarhical Regression. - Anton Agafonov; Vladislav V. Myasnikov (ITSC, 2015)

Structural Optimization of the Travel Time Prediction Model Based on Hierarchical Regression. - Anton Agafonov; Vladislav V. Myasnikov (AIST (Supplement), 2016)

Reliable routing in stochastic time-dependent network with the use of actual and forecast information of the traffic flows. - Anton Agafonov; Vladislav V. Myasnikov (Intelligent Vehicles Symposium, 2016)

Short-Term Traffic Flow Forecasting Using a Distributed Spatial-Temporal k Nearest Neighbors Model. - Anton Agafonov; Alexander Yumaganov (CSE, 2018)

Spatial-Temporal K Nearest Neighbors Model on MapReduce for Traffic Flow Prediction. - Anton Agafonov; Alexander Yumaganov (IDEAL (1), 2018)

Stochastic On-time Arrival Problem with Levy Stable Distributions. - Anton Agafonov; Vladislav V. Myasnikov (ICITE, 2019)

Bus Arrival Time Prediction with LSTM Neural Network. - Anton Agafonov; Alexander Yumaganov (ISNN (1), 2019)

Map Matching Algorithm Based on Dynamic Programming Approach. - Alexander Yumaganov; Anton Agafonov; Vladislav V. Myasnikov (FedCSIS, 2020)

An Improved Map Matching Algorithm Based on Dynamic Programming Approach. - Alexander Yumaganov; Anton Agafonov; Vladislav V. Myasnikov (ISM@FedCSIS, 2020)

Traffic Signal Control: a Double Q-learning Approach. - Anton Agafonov; Vladislav V. Myasnikov (FedCSIS, 2021)

Ontology Concept Extraction Algorithm for Deep Neural Networks. - Andrew Ponomarev; Anton Agafonov (FRUCT, 2022)

Ontology-Based Post-Hoc Explanations via Simultaneous Concept Extraction. - Andrew Ponomarev; Anton Agafonov (ICMLA, 2022)

An Experiment on Localization of Ontology Concepts in Deep Convolutional Neural Networks. - Anton Agafonov; Andrew Ponomarev (SoICT, 2022)

RevelioNN: Retrospective Extraction of Visual and Logical Insights for Ontology-Based Interpretation of Neural Networks. - Anton Agafonov; Andrew Ponomarev (FRUCT, 2023)

Ontology-Based Post-Hoc Neural Network Explanations Via Simultaneous Concept Extraction. - Andrew Ponomarev; Anton Agafonov (IntelliSys (2), 2023)

User Perception of Ontology-Based Explanations of AI Models. - Anton Agafonov; Andrew Ponomarev; Alexander V. Smirnov 001 (CHIRA (2), 2024)

Ontology-Based Explanations of Neural Networks: A User Perspective. - Andrew Ponomarev; Anton Agafonov (HCI (51), 2024)

Studying Trustworthiness of Neural-Symbolic Models for Enterprise Model Classification via Post-Hoc Explanation. - Alexander V. Smirnov 001; Anton Agafonov; Nikolay Shilov 001 (ICEIS (1), 2024)

Ontology-Based Neuro-Symbolic AI: Effects on Prediction Quality and Explainability. - Alexander V. Smirnov 001; Andrew Ponomarev; Anton Agafonov (IEEE Access, 2024)

STMPL: Human Soft-Tissue Simulation. - Anton Agafonov; Lihi Zelnik-Manor (CoRR, 2024)