| Beyond the Imitation Game: Quantifying and Extrapolating the Capabilities of Language Models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... Transactions on Machine Learning Research, 1-95, 2023 | 2234 | 2023 |
| A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part I: Models and Data Transformations D Kleyko, D Rachkovskij, E Osipov, A Rahimi ACM Computing Surveys (CSUR) 55 (6), 1-40, 2022 | 219 | 2022 |
| A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges D Kleyko, D Rachkovskij, E Osipov, A Rahimi ACM Computing Surveys (CSUR) 55 (9), 1-52, 2023 | 205 | 2023 |
| High-dimensional Computing as a Nanoscalable Paradigm A Rahimi, S Datta, D Kleyko, EP Frady, B Olshausen, P Kanerva, ... IEEE Transactions on Circuits and Systems I: Regular Papers 64 (9), 2508-2521, 2017 | 182 | 2017 |
| Vector Symbolic Architectures as a Computing Framework for Emerging Hardware D Kleyko, M Davies, EP Frady, P Kanerva, SJ Kent, BA Olshausen, ... Proceedings of the IEEE 110 (10), 1538-1571, 2022 | 148 | 2022 |
| Classification and Recall with Binary Hyperdimensional Computing: Tradeoffs in Choice of Density and Mapping Characteristics D Kleyko, A Rahimi, DA Rachkovskij, E Osipov, JM Rabaey IEEE Transactions on Neural Networks and Learning Systems 29 (12), 5880-5898, 2018 | 146 | 2018 |
| An Automated Machine Learning Approach for Smart Waste Management Systems D Rutqvist, D Kleyko, F Blomstedt IEEE Transactions on Industrial Informatics 16 (1), 384-392, 2020 | 128 | 2020 |
| A Theory of Sequence Indexing and Working Memory in Recurrent Neural Networks EP Frady, D Kleyko, FT Sommer Neural Computation 30 (6), 1449-1513, 2018 | 123 | 2018 |
| The Neurobench Framework for Benchmarking Neuromorphic Computing Algorithms and Systems J Yik, K Van den Berghe, D den Blanken, Y Bouhadjar, M Fabre, ... Nature Communications 16, 1545, 2025 | 120* | 2025 |
| Holographic Graph Neuron: A Bioinspired Architecture for Pattern Processing D Kleyko, E Osipov, A Senior, AI Khan, YA Şekercioğlu IEEE Transactions on Neural Networks and Learning Systems 28 (6), 1250-1262, 2017 | 102 | 2017 |
| NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation KD Dhole, V Gangal, S Gehrmann, A Gupta, Z Li, S Mahamood, ... Northern European Journal of Language Technology (NEJLT) 9 (1), 1-41, 2023 | 97 | 2023 |
| Computing on Functions Using Randomized Vector Representations (in brief) EP Frady, D Kleyko, CJ Kymn, BA Olshausen, FT Sommer 2022 Annual Neuro-Inspired Computational Elements Conference, 115-122, 2022 | 94 | 2022 |
| Efficient Optimization with Higher-order Ising Machines C Bybee, D Kleyko, DE Nikonov, A Khosrowshahi, BA Olshausen, ... Nature Communications 14 (1), 6033, 2023 | 85 | 2023 |
| Variable Binding for Sparse Distributed Representations: Theory and Applications EP Frady, D Kleyko, FT Sommer IEEE Transactions on Neural Networks and Learning Systems 34 (5), 2191-2204, 2023 | 81 | 2023 |
| AI-based Malicious Network Traffic Detection in VANETs N Lyamin, D Kleyko, Q Delooz, A Vinel IEEE Network 32 (6), 15-21, 2018 | 77 | 2018 |
| Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architectures M Heddes, I Nunes, P Vergés, D Kleyko, D Abraham, T Givargis, ... Journal of Machine Learning Research 24 (255), 1-10, 2023 | 73* | 2023 |
| Integer Echo State Networks: Efficient Reservoir Computing for Digital Hardware D Kleyko, EP Frady, M Kheffache, E Osipov IEEE Transactions on Neural Networks and Learning Systems 33 (4), 1688-1701, 2022 | 68* | 2022 |
| Real-time Jamming DoS Detection in Safety-critical V2V C-ITS Using Data Mining N Lyamin, D Kleyko, Q Delooz, A Vinel IEEE Communications Letters 23 (3), 442-445, 2019 | 63 | 2019 |
| Density Encoding Enables Resource-Efficient Randomly Connected Neural Networks D Kleyko, M Kheffache, EP Frady, U Wiklund, E Osipov IEEE Transactions on Neural Networks and Learning Systems 32 (8), 3777-3783, 2021 | 61 | 2021 |
| Imitation of Honey Bees’ Concept Learning Processes Using Vector Symbolic Architectures D Kleyko, E Osipov, RW Gayler, AI Khan, AG Dyer Biologically Inspired Cognitive Architectures 14, 57-72, 2015 | 61 | 2015 |
Evgeny OsipovProfessor, Luleå University of TechnologyVerified email at ltu.se
