Artem Babenko

2024²

• Chapter Егиазарян В. Г., Панферов А. Д., Кузнеделев Д. Д., Babenko A. Extreme Compression of Large Language Models via Additive Quantization, in: Proceedings of the 12th International Conference on Learning Representations (ICLR 2024). ICLR, 2024. P. 1-18. (in press)
• Chapter Babenko A., Баранчук Д. А., Стародубцев Н. О., Федоров А. Р. Your Student is Better Than Expected: Adaptive Teacher-Student Collaboration for Text-Conditional Diffusion Models, in: The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024. CVPR, 2024. P. 1-23. (in press)

2023⁵

• Chapter Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova. A critical look at the evaluation of GNNs under heterophily: are we really making progress?, in: Proceedings of the 11th International Conference on Learning Representations (ICLR 2023). ICLR, 2023. doi
• Chapter Oleg Platonov, Denis Kuznedelev, Babenko A., Prokhorenkova L. Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond, in: Advances in Neural Information Processing Systems 36 (NeurIPS 2023). Curran Associates, Inc., 2023.
• Chapter Bazhenov G., Kuznedelev D., Malinin A., Babenko A., Prokhorenkova L. Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts, in: Advances in Neural Information Processing Systems 36 (NeurIPS 2023). Curran Associates, Inc., 2023. P. 75567-75594.
• Chapter Anton Voronov, Mikhail Khoroshikh, Artem Babenko, Max Ryabinin. Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics, in: Advances in Neural Information Processing Systems 36 (NeurIPS 2023). Curran Associates, Inc., 2023. Ch. 1. P. 37491-37510. doi
• Preprint Gorishniy Y., Rubachev Ivan, Kartashev Nikolay, Kotelnikov A., Babenko A., Шлёнский Д. А. TabR: Tabular Deep Learning Meets Nearest Neighbors / arxiv. Series 2307 "14338v2". 2023. doi

2022²

• Chapter Baranchuk D., Rubachev I., Voynov A., Khrulkov V., Babenko A. Label-Efficient Semantic Segmentation with Diffusion Models, in: Proceedings of the 10th International Conference on Learning Representations (ICLR 2022). ICLR, 2022.
• Chapter Gorishniy Y., Ivan Rubachev, Babenko A. On Embeddings for Numerical Features in Tabular Deep Learning, in: Thirty-Sixth Conference on Neural Information Processing Systems : NeurIPS 2022. Curran Associates, Inc., 2022. Ch. 1. P. 24991-25004.

2021⁷

• Chapter Khrulkov V., Babenko A., Oseledets I. Functional Space Analysis of Local GAN Convergence, in: Proceedings of the 38th International Conference on Machine Learning (ICML 2021) Vol. 139. PMLR, 2021. P. 5432-5442.
• Chapter Khrulkov V., Mirvakhabova L., Oseledets I., Babenko A. Latent Transformations via NeuralODEs for GAN-based Image Editing, in: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021. , 2021. P. 14428-14437.
• Chapter Cherepkov A., Voynov A., Babenko A. Navigating the GAN Parameter Space for Semantic Image Editing, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021. IEEE, 2021. P. 3671-3680.
• Chapter Khrulkov V., Babenko A. Neural Side-by-Side: Predicting Human Preferences for No-Reference Super-Resolution Evaluation, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021. IEEE, 2021. P. 4988-4997.
• Chapter Voynov A., Morozov S., Babenko A. Object Segmentation Without Labels with Large-Scale Generative Models, in: Proceedings of the 38th International Conference on Machine Learning (ICML 2021) Vol. 139. PMLR, 2021. P. 10596-10606.
• Chapter Morozov S., Voynov A., Babenko A. On Self-Supervised Image Representations for GAN Evaluation, in: Proceedings of the 9th International Conference on Learning Representations (ICLR 2021). ICLR, 2021.. ICLR, 2021. P. 1-17.
• Chapter Gorishniy Y., Rubachev I., Khrulkov V., Babenko A. Revisiting Deep Learning Models for Tabular Data, in: Advances in Neural Information Processing Systems 34 (NeurIPS 2021). Curran Associates, Inc., 2021. P. 18932-18943.

2020³

• Chapter Sinitsin A., Plokhotnyuk V., Pyrkin D., Popov S., Babenko A. Editable Neural Networks, in: Proceedings of the 8th International Conference on Learning Representations (ICLR 2020). ICLR, 2020. P. 1-12.
• Chapter Popov S., Morozov S., Babenko A. Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data, in: Proceedings of the 8th International Conference on Learning Representations (ICLR 2020). ICLR, 2020. P. 1-12.
• Chapter Voynov A., Babenko A. Unsupervised Discovery of Interpretable Directions in the GAN Latent Space, in: International Conference on Machine Learning (ICML 2020) Vol. 119. PMLR, 2020. P. 9728-9738.

2019³

• Chapter Mazur D., Egiazarian V., Morozov S., Babenko A. Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs, in: Advances in Neural Information Processing Systems 32 (NeurIPS 2019). , 2019. P. 1-11.
• Chapter Баранчук Д. А., Persiyanov D., Sinitsin A., Babenko A. Learning to Route in Similarity Graphs, in: International Conference on Machine Learning (ICML 2019). PMLR, 2019. P. 475-484.
• Chapter Morozov S., Babenko A. Unsupervised neural quantization for compressed-domain similarity search, in: Proceedings of the IEEE International Conference on Computer Vision (ICCV 2019). IEEE, 2019. P. 3036-3045.

2018¹

2017²

• Chapter Babenko A., Lempitsky V. AnnArbor: Approximate Nearest Neighbors Using Arborescence Coding, in: Proceedings of the IEEE International Conference on Computer Vision (ICCV 2017). Venice : IEEE, 2017. P. 4885-4893. doi
• Chapter Babenko A., Lempitsky V. Product Split Trees, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017). Curran Associates, Inc., 2017. P. 2055-2063.

2016¹

2015³

• Chapter Babenko A., Lempitsky V. Aggregating Local Deep Features for Image Retrieval, in: Proceedings of the IEEE International Conference on Computer Vision (ICCV 2015). Santiago de Chile : IEEE, 2015. P. 1269-1277.
• Article Babenko A., Lempitsky V. The inverted multi-index // IEEE Transactions on Pattern Analysis and Machine Intelligence. 2015. Vol. 37. No. 6. P. 1247-1260.
• Chapter Babenko A., Lempitsky V. Tree Quantization for Large-Scale Similarity Search and Classification, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVRP 2015). Curran Associates, Inc., 2015. P. 4240-4248.

2014³

• Chapter Babenko A., Lempitsky V. Additive Quantization for Extreme Vector Compression, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014). Columbus : IEEE Computer Society, 2014. P. 931-938.
• Chapter Babenko A., Slesarev A., Chigorin A., Lempitsky V. Neural Codes for Image Retrieval, in: Lecture Notes in Computer Science. Proceedings of the 13th European Conference on Computer Vision (ECCV 2014) Vol. 8689. Part 1. Zürich : Springer, 2014. P. 584-599.
• Article Babenko A. The Inverted Multi-Index // IEEE Transactions on Pattern Analysis and Machine Intelligence. 2014. Vol. PP. No. 99. P. 1.

2012¹