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Boris Knyazev
Boris Knyazev
Research Scientist, Samsung - SAIT AI Lab
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
3242019
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
135*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
1062018
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
722021
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
652021
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
58*2020
Image Classification with Hierarchical Multigraph Networks
B Knyazev, X Lin, MR Amer, GW Taylor
British Machine Vision Conference (BMVC), 2019
46*2019
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
392018
Learning temporal attention in dynamic graphs with bilinear interactions
B Knyazev, C Augusta, GW Taylor
Plos one 16 (3), e0247936, 2021
322021
On Evaluation Metrics for Graph Generative Models
R Thompson, B Knyazev, E Ghalebi, J Kim, GW Taylor
International Conference on Learning Representations (ICLR), 2022
312022
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
25*2021
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
21*2022
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
162022
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
132021
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
Understanding Attention in Graph Neural Networks
B Knyazev, G Taylor, M Amer
Proceedings of the ICLR RLGM Workshop, 2019
7*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
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
52023
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
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Articles 1–20