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2020 – today
- 2024
[j1]Alexander V. Smirnov
, Andrew Ponomarev, Anton Agafonov:
Ontology-Based Neuro-Symbolic AI: Effects on Prediction Quality and Explainability. IEEE Access 12: 156609-156626 (2024)- [c18]Andrew Ponomarev, Anton Agafonov:
Ontology-Based Explanations of Neural Networks: A User Perspective. HCI (51) 2024: 264-276 - [c17]Alexander V. Smirnov, Anton Agafonov, Nikolay Shilov:
Studying Trustworthiness of Neural-Symbolic Models for Enterprise Model Classification via Post-Hoc Explanation. ICEIS (1) 2024: 873-880 - [i1]Anton Agafonov, Lihi Zelnik-Manor:
STMPL: Human Soft-Tissue Simulation. CoRR abs/2403.08344 (2024) - 2023
- [c16]Anton Agafonov, Andrew Ponomarev:
RevelioNN: Retrospective Extraction of Visual and Logical Insights for Ontology-Based Interpretation of Neural Networks. FRUCT 2023: 3-9 - [c15]Andrew Ponomarev, Anton Agafonov:
Ontology-Based Post-Hoc Neural Network Explanations Via Simultaneous Concept Extraction. IntelliSys (2) 2023: 433-446 - 2022
- [c14]Andrew Ponomarev, Anton Agafonov:
Ontology Concept Extraction Algorithm for Deep Neural Networks. FRUCT 2022: 221-226 - [c13]Andrew Ponomarev, Anton Agafonov:
Ontology-Based Post-Hoc Explanations via Simultaneous Concept Extraction. ICMLA 2022: 887-890 - [c12]Anton Agafonov, Andrew Ponomarev:
An Experiment on Localization of Ontology Concepts in Deep Convolutional Neural Networks. SoICT 2022: 82-87 - 2021
- [c11]Anton Agafonov, Vladislav V. Myasnikov:
Traffic Signal Control: a Double Q-learning Approach. FedCSIS 2021: 365-369 - 2020
- [c10]Alexander Yumaganov, Anton Agafonov, Vladislav V. Myasnikov:
An Improved Map Matching Algorithm Based on Dynamic Programming Approach. ISM@FedCSIS 2020: 87-102 - [c9]Alexander Yumaganov, Anton Agafonov, Vladislav V. Myasnikov:
Map Matching Algorithm Based on Dynamic Programming Approach. FedCSIS 2020: 563-566
2010 – 2019
- 2019
- [c8]Anton Agafonov, Vladislav V. Myasnikov:
Stochastic On-time Arrival Problem with Levy Stable Distributions. ICITE 2019: 227-231 - [c7]Anton Agafonov, Alexander Yumaganov:
Bus Arrival Time Prediction with LSTM Neural Network. ISNN (1) 2019: 11-18 - 2018
- [c6]Anton Agafonov, Alexander Yumaganov:
Short-Term Traffic Flow Forecasting Using a Distributed Spatial-Temporal k Nearest Neighbors Model. CSE 2018: 91-98 - [c5]Anton Agafonov, Alexander Yumaganov:
Spatial-Temporal K Nearest Neighbors Model on MapReduce for Traffic Flow Prediction. IDEAL (1) 2018: 253-260 - 2016
- [c4]Anton Agafonov, Vladislav V. Myasnikov:
Structural Optimization of the Travel Time Prediction Model Based on Hierarchical Regression. AIST (Supplement) 2016: 1-9 - [c3]Anton Agafonov, Vladislav V. Myasnikov:
Reliable routing in stochastic time-dependent network with the use of actual and forecast information of the traffic flows. Intelligent Vehicles Symposium 2016: 1168-1172 - 2015
- [c2]Anton Agafonov, Vladislav V. Myasnikov:
Traffic Flow Forecasting Algorithm Based on Combination of Adaptive Elementary Predictors. AIST 2015: 163-174 - [c1]Anton Agafonov, Vladislav V. Myasnikov:
An Adaptive Algorithm for Public Transport Arrival Time Prediction Based on Hierarhical Regression. ITSC 2015: 2776-2781
Coauthor Index
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