Human nonverbal behavior multi-sourced ontological annotation. - Boris Knyazev 001 (VIGTA@ICVS, 2013)

Autoconvolution for Unsupervised Feature Learning. - Boris Knyazev 001; Erhardt Barth; Thomas Martinetz (CoRR, 2016)

Recursive autoconvolution for unsupervised learning of convolutional neural networks. - Boris Knyazev 001; Erhardt Barth; Thomas Martinetz (IJCNN, 2017)

Convolutional neural networks pretrained on large face recognition datasets for emotion classification from video. - Boris Knyazev 001; Roman Shvetsov; Natalia Efremova; Artem Kuharenko (CoRR, 2017)

Leveraging Large Face Recognition Data for Emotion Classification. - Boris Knyazev 001; Roman Shvetsov; Natalia Efremova; Artem Kuharenko (FG, 2018)

Dominant and Complementary Emotion Recognition From Still Images of Faces. - Jianzhu Guo; Zhen Lei 001; Jun Wan 001; Egils Avots; Noushin Hajarolasvadi; Boris Knyazev 001; Artem Kuharenko; Júlio Cezar Silveira Jacques Júnior; Xavier Baró; Hasan Demirel; Sergio Escalera; Juri Allik; et al. (IEEE Access, 2018)

Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules. - Boris Knyazev 001; Xiao Lin; Mohamed R. Amer; Graham W. Taylor (CoRR, 2018)

Image Classification with Hierarchical Multigraph Networks. - Boris Knyazev 001; Xiao Lin; Mohamed R. Amer; Graham W. Taylor (BMVC, 2019)

Understanding Attention and Generalization in Graph Neural Networks. - Boris Knyazev 001; Graham W. Taylor; Mohamed R. Amer (NeurIPS, 2019)

Understanding attention in graph neural networks. - Boris Knyazev 001; Graham W. Taylor; Mohamed R. Amer (CoRR, 2019)

Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions. - Boris Knyazev 001; Carolyn Augusta; Graham W. Taylor (CoRR, 2019)

Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (BMVC, 2020)

Generative Graph Perturbations for Scene Graph Prediction. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (CoRR, 2020)

Generative Compositional Augmentations for Scene Graph Prediction. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (ICCV, 2021)

Context-aware Scene Graph Generation with Seq2Seq Transformers. - Yichao Lu; Himanshu Rai; Jason Chang; Boris Knyazev 001; Guangwei Yu; Shashank Shekhar 005; Graham W. Taylor; Maksims Volkovs (ICCV, 2021)

Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning. - Hyunsoo Chung; Jungtaek Kim 001; Boris Knyazev 001; Jinhwi Lee; Graham W. Taylor; Jaesik Park; Minsu Cho (NeurIPS, 2021)

Parameter Prediction for Unseen Deep Architectures. - Boris Knyazev 001; Michal Drozdzal; Graham W. Taylor; Adriana Romero-Soriano (NeurIPS, 2021)

On Evaluation Metrics for Graph Generative Models. - Rylee Thompson; Boris Knyazev 001; Elahe Ghalebi; Jungtaek Kim 001; Graham W. Taylor (ICLR, 2022)

Pretraining a Neural Network before Knowing Its Architecture. - Boris Knyazev 001 (CoRR, 2022)

Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models? - Boris Knyazev 001; Doha Hwang; Simon Lacoste-Julien (ICML, 2023)

Can We Learn Communication-Efficient Optimizers? - Charles-Étienne Joseph; Benjamin Thérien; Abhinav Moudgil; Boris Knyazev 001; Eugene Belilovsky (CoRR, 2023)

Graph Neural Networks for Learning Equivariant Representations of Neural Networks. - Miltiadis Kofinas; Boris Knyazev 001; Yan Zhang; Yunlu Chen; Gertjan J. Burghouts; Efstratios Gavves; Cees G. M. Snoek; David W. Zhang (ICLR, 2024)

LoGAH: Predicting 774-Million-Parameter Transformers using Graph HyperNetworks with 1/100 Parameters. - Xinyu Zhou; Boris Knyazev 001; Alexia Jolicoeur-Martineau; Jie Fu (CoRR, 2024)

μLO: Compute-Efficient Meta-Generalization of Learned Optimizers. - Benjamin Thérien; Charles-Étienne Joseph; Boris Knyazev 001; Edouard Oyallon; Irina Rish; Eugene Belilovsky (CoRR, 2024)

Any-Property-Conditional Molecule Generation with Self-Criticism using Spanning Trees. - Alexia Jolicoeur-Martineau; Aristide Baratin; Kisoo Kwon; Boris Knyazev 001; Yan Zhang (CoRR, 2024)

CNN Wild Park - Graph Neural Networks for Learning Equivariant Representations of Neural Networks. - Miltiadis Kofinas; Boris Knyazev 001; Yan Zhang; Yunlu Chen; Gertjan J. Burghouts; Efstratios Gavves; Cees Snoek; David W. Zhang (Zenodo, 2024)

Accelerating Training with Neuron Interaction and Nowcasting Networks. - Boris Knyazev 001; Abhinav Moudgil; Guillaume Lajoie; Eugene Belilovsky; Simon Lacoste-Julien (ICLR, 2025)

Meta-learning Optimizers for Communication-Efficient Learning. - Charles-Étienne Joseph; Benjamin Thérien; Abhinav Moudgil; Boris Knyazev 001; Eugene Belilovsky (Trans. Mach. Learn. Res., 2025)

Celo: Training Versatile Learned Optimizers on a Compute Diet. - Abhinav Moudgil; Boris Knyazev 001; Guillaume Lajoie; Eugene Belilovsky (Trans. Mach. Learn. Res., 2025)

Learning Versatile Optimizers on a Compute Diet. - Abhinav Moudgil; Boris Knyazev 001; Guillaume Lajoie; Eugene Belilovsky (CoRR, 2025)

Generating π-Functional Molecules Using STGG+ with Active Learning. - Alexia Jolicoeur-Martineau; Yan Zhang; Boris Knyazev 001; Aristide Baratin; Cheng-Hao Liu (CoRR, 2025)