| Understanding attention and generalization in graph neural networks B Knyazev, GW Taylor, MR Amer Advances in Neural Information Processing Systems, 4204-4214, 2019 | 404 | 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 | 145* | 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 | 115 | 2018 |
| 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 | 92 | 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 | 88 | 2021 |
| 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 | 62* | 2020 |
| Image Classification with Hierarchical Multigraph Networks B Knyazev, X Lin, MR Amer, GW Taylor British Machine Vision Conference (BMVC), 2019 | 49* | 2019 |
| On Evaluation Metrics for Graph Generative Models R Thompson, B Knyazev, E Ghalebi, J Kim, GW Taylor International Conference on Learning Representations (ICLR), 2022 | 44 | 2022 |
| 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 | 44 | 2018 |
| Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights K Schürholt, B Knyazev, X Giró-i-Nieto, D Borth Advances in Neural Information Processing Systems, 2022 | 42* | 2022 |
| Learning temporal attention in dynamic graphs with bilinear interactions B Knyazev, C Augusta, GW Taylor Plos one 16 (3), e0247936, 2021 | 39 | 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 | 29* | 2021 |
| Model Zoo: A Dataset of Diverse Populations of Neural Network Models K Schürholt, D Taskiran, B Knyazev, X Giró-i-Nieto, D Borth Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks, 2022 | 28 | 2022 |
| Graph Neural Networks for Learning Equivariant Representations of Neural Networks M Kofinas, B Knyazev, Y Zhang, Y Chen, GJ Burghouts, E Gavves, ... International Conference on Learning Representations (ICLR), 2024 | 27 | 2024 |
| 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 | 23 | 2021 |
| Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models? B Knyazev, D Hwang, S Lacoste-Julien International Conference on Machine Learning (ICML) 202, 17243-17259, 2023 | 16 | 2023 |
| 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 | 9* | 2017 |
| Understanding Attention in Graph Neural Networks B Knyazev, G Taylor, M Amer Proceedings of the ICLR RLGM Workshop, 2019 | 8* | 2019 |
| 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 |
| 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 | 4* | 2014 |
Graham TaylorUniversity of Guelph and Vector Institute for Artificial Intelligence確認したメール アドレス: uoguelph.ca