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Boris Knyazev
Boris Knyazev
Research Scientist, Samsung - SAIT AI Lab, Montreal
Verified email at samsung.com - Homepage
Title
Cited by
Cited by
Year
Understanding attention and generalization in graph neural networks
B Knyazev, GW Taylor, MR Amer
Advances in Neural Information Processing Systems, 4204-4214, 2019
1792019
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
117*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
832018
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
40*2020
Image Classification with Hierarchical Multigraph Networks
B Knyazev, X Lin, MR Amer, GW Taylor
British Machine Vision Conference (BMVC), 2019
38*2019
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
322021
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
312018
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
292021
Learning temporal attention in dynamic graphs with bilinear interactions
B Knyazev, C Augusta, GW Taylor
Plos one 16 (3), e0247936, 2021
19*2021
On Evaluation Metrics for Graph Generative Models
R Thompson, B Knyazev, E Ghalebi, J Kim, GW Taylor
International Conference on Learning Representations (ICLR), 2022
122022
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
8*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
72017
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
62021
Understanding Attention in Graph Neural Networks
B Knyazev, G Taylor, M Amer
Proceedings of the ICLR RLGM Workshop, 2019
6*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
62012
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
42014
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
32013
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
22022
Hyper-Representations for Pre-Training and Transfer Learning
K Schürholt, B Knyazev, X Giró-i-Nieto, D Borth
ICML Workshop of Pre-training: Perspectives, Pitfalls, and Paths Forward, 2022
22022
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