| Understanding attention and generalization in graph neural networks B Knyazev, GW Taylor, MR Amer Advances in Neural Information Processing Systems, 4204-4214, 2019 | 141 | 2019 |
| Leveraging large face recognition data for emotion classification B Knyazev, R Shvetsov, N Efremova, A Kuharenko 2018 13th IEEE International Conference on Automatic Face & Gesture …, 2018 | 102* | 2018 |
| Dominant and complementary emotion recognition from still images of faces J Guo, Z Lei, J Wan, E Avots, N Hajarolasvadi, B Knyazev, A Kuharenko, ... IEEE Access 6, 26391-26403, 2018 | 68 | 2018 |
| Image Classification with Hierarchical Multigraph Networks B Knyazev, X Lin, MR Amer, GW Taylor British Machine Vision Conference (BMVC), 2019 | 30* | 2019 |
| Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation B Knyazev, H de Vries, C Cangea, GW Taylor, A Courville, E Belilovsky British Machine Vision Conference (BMVC), 2020 | 29* | 2020 |
| Spectral multigraph networks for discovering and fusing relationships in molecules B Knyazev, X Lin, MR Amer, GW Taylor NeurIPS Workshop on Machine Learning for Molecules and Materials, 2018 | 27 | 2018 |
| Learning temporal attention in dynamic graphs with bilinear interactions B Knyazev, C Augusta, GW Taylor Plos one 16 (3), e0247936, 2021 | 13* | 2021 |
| Parameter prediction for unseen deep architectures B Knyazev, M Drozdzal, GW Taylor, A Romero Soriano Advances in Neural Information Processing Systems 34, 29433-29448, 2021 | 12 | 2021 |
| Context-aware Scene Graph Generation with Seq2Seq Transformers Y Lu, H Rai, J Chang, B Knyazev, G Yu, S Shekhar, GW Taylor, M Volkovs International Conference on Computer Vision (ICCV), 2021 | 11 | 2021 |
| Recursive autoconvolution for unsupervised learning of convolutional neural networks B Knyazev, E Barth, T Martinetz 2017 International Joint Conference on Neural Networks (IJCNN), 2486-2493, 2017 | 8 | 2017 |
| Applying an ontology approach and Kinect SDK to human posture description AA Nekhina, BA Knyazev, LH Kashapova, IN Spiridonov Biomeditsinskaia radioelektronika= Biomedical Radioelectronics, 54-60, 2012 | 6 | 2012 |
| Understanding Attention in Graph Neural Networks B Knyazev, G Taylor, M Amer Proceedings of the ICLR RLGM Workshop, 2019 | 4* | 2019 |
| Методика и модель кластеризации паттернов двигательной активности лица как преобразований метаграфов БА Князев, ВМ Черненький Вестник МГТУ им. НЭ Баумана. Сер. Приборостроение, 34-54, 2014 | 4 | 2014 |
| Brick-by-Brick: Combinatorial construction with deep reinforcement learning H Chung, J Kim, B Knyazev, J Lee, GW Taylor, J Park, M Cho Advances in Neural Information Processing Systems 34, 5745-5757, 2021 | 3 | 2021 |
| Generative Compositional Augmentations for Scene Graph Prediction B Knyazev, H de Vries, C Cangea, GW Taylor, A Courville, E Belilovsky International Conference on Computer Vision (ICCV), 2021 | 3* | 2021 |
| Convolutional Sparse Coding for Static and Dynamic Images Analysis. BA Knyazev, VM Chernenkiy Science & Education of Bauman MSTU/Nauka i Obrazovanie of Bauman MSTU, 2014 | 3* | 2014 |
| Human nonverbal behavior multi-sourced ontological annotation B Knyazev International Workshop on Video and Image Ground Truth in Computer Vision …, 2013 | 3 | 2013 |
| Graph Classification with Graph Convolutional Networks in PyTorch B Knyazev GitHub: https://github.com/bknyaz/graph_nn, 2018 | 2 | 2018 |
| On Evaluation Metrics for Graph Generative Models R Thompson, B Knyazev, E Ghalebi, J Kim, GW Taylor International Conference on Learning Representations (ICLR), 2022 | 1 | 2022 |
| Generative Graph Perturbations for Scene Graph Prediction B Knyazev, H de Vries, C Cangea, GW Taylor, A Courville, E Belilovsky ICML Workshop on Object-Oriented Learning (OOL): Perception, Representation …, 2020 | 1 | 2020 |
Graham TaylorUniversity of Guelph and Vector Institute for Artificial IntelligenceVerified email at uoguelph.ca
