The Object-Oriented Approach to the Medical Real Time System Design. - Sergei B. Arseniev; Mikhail V. Kiselev (MIE, 1991)

PolyAnalyst - A Machine Discovery System Inferring Functional Programs. - Mikhail V. Kiselev (KDD Workshop, 1994)

Regression-Based Classification Methods and Their Comparisons with Desision Tree Algorithms. - Mikhail V. Kiselev; Sergei M. Ananyan; Sergei B. Arseniev (PKDD, 1997)

PolyAnalyst Data Analysis Technique and Its Specialization for Processing Data Organized as a Set of Attribute Values. - Mikhail V. Kiselev; Sergei M. Ananyan; Sergei B. Arseniev (PKDD, 1998)

LA - A Clustering Algorithm with an Automated Selection of Attributes, wich is Invariant to Functional Transformations of Coordinates. - Mikhail V. Kiselev; Sergei M. Ananyan; Sergei B. Arseniev (PKDD, 1999)

Statistical approach to unsupervised recognition of spatio-temporal patterns by spiking neurons. - Mikhail V. Kiselev (IJCNN, 2003)

Self-organized spiking neural network recognizing phase/frequency correlations. - Mikhail V. Kiselev (IJCNN, 2009)

Self-organized Short-Term Memory Mechanism in Spiking Neural Network. - Mikhail V. Kiselev (ICANNGA (1), 2011)

Self-Organization Process in Large Spiking Neural Networks Leading to Formation of Working Memory Mechanism. - Mikhail V. Kiselev (IWANN (1), 2013)

Input-output Characteristics of LIF Neuron with Dynamic Threshold and Short Term Synaptic Depression. - Mikhail V. Kiselev (ANNIIP, 2014)

Empirical Models as a Basis for Synthesis of Large Spiking Neural Networks with Pre-Specified Properties. - Mikhail V. Kiselev (IJCCI (NCTA), 2014)

Homogenous Chaotic Network Serving as a Rate/Population Code to Temporal Code Converter. - Mikhail V. Kiselev (Comput. Intell. Neurosci., 2014)

Rate coding vs. temporal coding - is optimum between? - Mikhail V. Kiselev (IJCNN, 2016)

Conversion from Rate Code to Temporal Code - Crucial Role of Inhibition. - Mikhail V. Kiselev (ISNN, 2016)

A synaptic plasticity rule providing a unified approach to supervised and unsupervised learning. - Mikhail V. Kiselev (IJCNN, 2017)

A Preprocessing Layer in Spiking Neural Networks - Structure, Parameters, Performance Criteria. - Mikhail V. Kiselev; Andrey Lavrentyev (IJCNN, 2019)

A Spiking Neural Network Structure Implementing Reinforcement Learning. - Mikhail V. Kiselev (CoRR, 2022)

Neuromorphic Artificial Intelligence Systems. - Dmitry Ivanov; Aleksandr Chezhegov; Andrey Grunin; Mikhail V. Kiselev; Denis A. Larionov (CoRR, 2022)

A Spiking Neural Network Learning Markov Chain. - Mikhail V. Kiselev (CoRR, 2022)

A Spiking Neural Network Learning Markov Chain. - Mikhail V. Kiselev; Alexander Ivanitsky; Andrey Lavrentyev (IJCNN, 2023)

A Spiking Binary Neuron - Detector of Causal Links. - Mikhail V. Kiselev; Denis A. Larionov; Andrey Urusov (CoRR, 2023)

From "What" to "When" - a Spiking Neural Network Predicting Rare Events and Time to their Occurrence. - Mikhail V. Kiselev (CoRR, 2023)

From "What" to "When" - a Spiking Neural Network Predicting Rare Events and Time to their Occurrence. - Mikhail V. Kiselev; Andrey Lavrentyev; Denis A. Larionov; Dmitry A. Ivanov (IJCNN, 2024)

A purely spiking approach to reinforcement learning. - Mikhail V. Kiselev; Alexander Ivanitsky; Denis A. Larionov (Cogn. Syst. Res., 2025)

Convolutional Spiking Neural Network for Image Classification. - Mikhail V. Kiselev; Andrey Lavrentyev (CoRR, 2025)