Boris Knyazev

About me

I’m a Research Scientist at Samsung - SAIT AI Lab. I completed my PhD at the Machine Learning Research Group, University of Guelph and Vector Institute under supervision of Graham Taylor in 2022. My research interests lie at the intersection of graph neural networks (GNNs), computer vision and meta-learning. In the past I interned at Facebook AI Research (FAIR) working with ‪Adriana Romero and Michal Drozdzal on parameter prediction for neural networks. I also interned at Mila working with Eugene Belilovsky and Aaron Courville on visual compositional generalization. I also interned at SRI International with Mohamed Amer, where I worked on training GNNs on image superpixels. Before starting my PhD, I worked on unsupervised learning and pretraining of neural networks, face, emotion and facial attributes recognition, and video recognition.

1 paper accepted as oral at ICLR 2024 openreview, arXiv, code, twitter
1 paper is accepted at NeurIPS 2023 workshop Learning Optimizers for Local SGD
2 papers are accepted at ICML 2023 workshops LLMs for Graphs, Learning to Optimize
1 paper accepted at ICML 2023 arXiv, code
1 paper accepted at NeurIPS 2022 Track Datasets and Benchmarks (openreview, arXiv, dataset)
1 paper accepted at NeurIPS 2022 (arXiv, NeurIPS)
My PhD thesis has been approved and is available online, LateX source
1 paper accepted at ICLR 2022 (openreview, arXiv, code)
2 out of 2 papers accepted at NeurIPS 2021
Selected as an “Outstanding Reviewer” for ICCV 2021 (top 5% student reviewers)
2 out of 2 papers accepted at ICCV 2021

2024: ICML, Neural Networks
2023: ICML, NeurIPs, MLG @ KDD, ICLR
2022: CVPR, ICML, ICML Workshop, NeurIPS, Learning on Graphs Conference (LoG), Nature Machine Intelligence
2021: ICCV
2020: BMVC, ICML Workshop on Graph Representation Learning and Beyond

See the full list at Google Scholar.

Parameter Prediction for Unseen Deep Architectures
Boris Knyazev, Michal Drozdzal, Graham W. Taylor, Adriana Romero-Soriano
Advances in Neural Information Processing Systems (NeurIPS), 2021
html, pdf, reviews, UofG news, Yannic Kilcher’s video, neurips video, code, Colab-predict, Colab-fine-tune, twitter, quantamagazine

Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning
Hyunsoo Chung, Jungtaek Kim, Boris Knyazev, Jinhwi Lee, Graham W. Taylor, Jaesik Park, Minsu Cho
Advances in Neural Information Processing Systems (NeurIPS), 2021
html, pdf, reviews, video, code

Context-aware Scene Graph Generation with Seq2Seq Transformers
Yichao Lu, Himanshu Rai, Jason Chang, Boris Knyazev, Shashank Shekhar, Graham W. Taylor, Maksims Volkovs
International Conference on Computer Vision (ICCV), 2021
html, pdf, code

Generative Compositional Augmentations for Scene Graph Prediction
Boris Knyazev, Harm de Vries, Cătălina Cangea, Graham W. Taylor, Aaron Courville, Eugene Belilovsky
International Conference on Computer Vision (ICCV), 2021
html, pdf, ICML Workshop version, ICML workshop video, ICCV code

Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation
Boris Knyazev, Harm de Vries, Cătălina Cangea, Graham W. Taylor, Aaron Courville, Eugene Belilovsky
British Machine Vision Conference (BMVC), 2020
html, pdf, bmvc, code, Data Fest tutorial

Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions
Boris Knyazev*, Carolyn Augusta*, Graham Taylor (*equal contribution)
PLOS ONE, 2021
html, pdf, plos one journal link, code

Understanding Attention and Generalization in Graph Neural Networks
Boris Knyazev, Graham Taylor, Mohamed Amer
Advances in Neural Information Processing Systems (NeurIPS), 2019
html, pdf, neurips, ICLR Workshop version, code, poster, slides

Image Classification with Hierarchical Multigraph Networks
Boris Knyazev, Xiao Lin, Mohamed Amer, Graham Taylor
British Machine Vision Conference (BMVC), 2019
html, pdf, bmvc pdf, code, blog post

Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules
Boris Knyazev, Xiao Lin, Mohamed Amer, Graham Taylor
NeurIPS Workshop on Machine Learning for Molecules and Materials, 2018
html, pdf, code

Leveraging Large Face Recognition Data for Emotion Classification
Boris Knyazev, Roman Shvetsov, Natalia Efremova, Artem Kuharenko
FG Workshop on Large-scale Emotion Recognition and Analysis (LERA), 2018
html, pdf, code, Top-2 in EmotiW 2017 challenge

Recursive Autoconvolution for Unsupervised Learning of Convolutional Neural Networks
Boris Knyazev, Erhardt Barth, Thomas Martinetz
International Joint Conference on Neural Networks (IJCNN), 2017
html, pdf, matlab code, python code, reddit

Last updated: Apr 2, 2024