| Label-Efficient Semantic Segmentation with Diffusion Models D Baranchuk, I Rubachev, A Voynov, V Khrulkov, A Babenko International Conference on Learning Representations, 2022, 2022 | 818 | 2022 |
| Tabddpm: Modelling tabular data with diffusion models A Kotelnikov, D Baranchuk, I Rubachev, A Babenko International Conference on Machine Learning, 2023, 2023 | 596 | 2023 |
| GP-VAE: Deep Probabilistic Time Series Imputation V Fortuin*, D Baranchuk*, G Rätsch, S Mandt Artificial Intelligence and Statistics (AISTATS), 2020, 2020 | 529 | 2020 |
| Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors D Baranchuk, A Babenko, Y Malkov The European Conference on Computer Vision (ECCV), 202-216, 2018 | 139 | 2018 |
| Results of the NeurIPS’21 challenge on billion-scale approximate nearest neighbor search HV Simhadri, G Williams, M Aumüller, M Douze, A Babenko, D Baranchuk, ... NeurIPS 2021 Competitions and Demonstrations Track, 177-189, 2022 | 118 | 2022 |
| Petals: Collaborative inference and fine-tuning of large models A Borzunov*, D Baranchuk*, T Dettmers*, M Ryabinin*, Y Belkada*, ... Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 117 | 2023 |
| Distributed inference and fine-tuning of large language models over the internet A Borzunov, M Ryabinin, A Chumachenko, D Baranchuk, T Dettmers, ... Advances in neural information processing systems 36, 12312-12331, 2023 | 103 | 2023 |
| Learning to Route in Similarity Graphs D Baranchuk, D Persiyanov, A Sinitsin, A Babenko Proceedings of the 36th International Conference on Machine Learning, PMLR …, 2019 | 52 | 2019 |
| Dedrift: Robust similarity search under content drift D Baranchuk, M Douze, Y Upadhyay, IZ Yalniz Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 17 | 2023 |
| Towards Similarity Graphs Constructed by Deep Reinforcement Learning D Baranchuk, A Babenko arXiv preprint arXiv:1911.12122, 2019 | 16 | 2019 |
| Switti: Designing scale-wise transformers for text-to-image synthesis A Voronov, D Kuznedelev, M Khoroshikh, V Khrulkov, D Baranchuk Computer Vision and Pattern Recognition (CVPR), 2025, 2025 | 15 | 2025 |
| Results of the Big ANN: NeurIPS'23 competition HV Simhadri, M Aumüller, A Ingber, M Douze, G Williams, MD Manohar, ... arXiv preprint arXiv:2409.17424, 2024 | 12 | 2024 |
| Invertible consistency distillation for text-guided image editing in around 7 steps N Starodubcev, M Khoroshikh, A Babenko, D Baranchuk Advances in Neural Information Processing Systems 37, 12496-12527, 2024 | 7 | 2024 |
| Your Student is Better Than Expected: Adaptive Teacher-Student Collaboration for Text-Conditional Diffusion Models N Starodubcev, A Fedorov, A Babenko, D Baranchuk Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 7 | 2024 |
| Distilling the Knowledge from Conditional Normalizing Flows D Baranchuk, V Aliev, A Babenko ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit …, 2021 | 7 | 2021 |
| Towards real-time text-driven image manipulation with unconditional diffusion models N Starodubcev, D Baranchuk, V Khrulkov, A Babenko arXiv preprint arXiv:2304.04344, 2023 | 5 | 2023 |
| Scale-wise Distillation of Diffusion Models N Starodubcev, D Kuznedelev, A Babenko, D Baranchuk arXiv preprint arXiv:2503.16397, 2025 | 3 | 2025 |
| Inverse Bridge Matching Distillation N Gushchin, D Li, D Selikhanovych, E Burnaev, D Baranchuk, A Korotin arXiv preprint arXiv:2502.01362, 2025 | 3 | 2025 |
| Yaart: Yet another art rendering technology S Kastryulin, A Konev, A Shishenya, E Lyapustin, A Khurshudov, ... Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and …, 2025 | 2 | 2025 |
| Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization M Persiianov, A Asadulaev, N Andreev, N Starodubcev, D Baranchuk, ... arXiv preprint arXiv:2410.02628, 2024 | 2 | 2024 |
Artem BabenkoYandexVerified email at yandex-team.ru
