Baranchuk, Dmitry

16 publications

NeurIPS 2025 Alchemist: Turning Public Text-to-Image Data into Generative Gold Valerii Startsev, Alexander Ustyuzhanin, Alexey Kirillov, Dmitry Baranchuk, Sergey Kastryulin

ICML 2025 Inverse Bridge Matching Distillation Nikita Gushchin, David Li, Daniil Selikhanovych, Evgeny Burnaev, Dmitry Baranchuk, Alexander Korotin

NeurIPS 2025 Results of the Big ANN: NeurIPS’23 Competition Harsha Vardhan Simhadri, Martin Aumüller, Matthijs Douze, Dmitry Baranchuk, Amir Ingber, Edo Liberty, George Williams, Ben Landrum, Magdalen Dobson Manohar, Mazin Karjikar, Laxman Dhulipala, Meng Chen, Yue Chen, Rui Ma, Kai Zhang, Yuzheng Cai, Jiayang Shi, Weiguo Zheng, Yizhuo Chen, Jie Yin, Ben Huang

NeurIPS 2024 Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps Nikita Starodubcev, Mikhail Khoroshikh, Artem Babenko, Dmitry Baranchuk

CVPR 2024 Your Student Is Better than Expected: Adaptive Teacher-Student Collaboration for Text-Conditional Diffusion Models Nikita Starodubcev, Dmitry Baranchuk, Artem Fedorov, Artem Babenko

ICCV 2023 DEDRIFT: Robust Similarity Search Under Content Drift Dmitry Baranchuk, Matthijs Douze, Yash Upadhyay, I. Zeki Yalniz

NeurIPS 2023 Distributed Inference and Fine-Tuning of Large Language Models over the Internet Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, Colin A Raffel

ICML 2023 TabDDPM: Modelling Tabular Data with Diffusion Models Akim Kotelnikov, Dmitry Baranchuk, Ivan Rubachev, Artem Babenko

ICLR 2022 Graph-Based Nearest Neighbor Search in Hyperbolic Spaces Liudmila Prokhorenkova, Dmitry Baranchuk, Nikolay Bogachev, Yury Demidovich, Alexander Kolpakov

ICLR 2022 Label-Efficient Semantic Segmentation with Diffusion Models Dmitry Baranchuk, Andrey Voynov, Ivan Rubachev, Valentin Khrulkov, Artem Babenko

NeurIPSW 2022 Petals: Collaborative Inference and Fine-Tuning of Large Models Alexander Borzunov, Dmitry Baranchuk, Tim Dettmers, Max Ryabinin, Younes Belkada, Artem Chumachenko, Pavel Samygin, Colin Raffel

ICMLW 2021 Discovering Weight Initializers with Meta Learning Dmitry Baranchuk, Artem Babenko

ICMLW 2021 Distilling the Knowledge from Conditional Normalizing Flows Dmitry Baranchuk, Vladimir Aliev, Artem Babenko

AISTATS 2020 GP-VAE: Deep Probabilistic Time Series Imputation Vincent Fortuin, Dmitry Baranchuk, Gunnar Raetsch, Stephan Mandt

ICML 2019 Learning to Route in Similarity Graphs Dmitry Baranchuk, Dmitry Persiyanov, Anton Sinitsin, Artem Babenko

ECCV 2018 Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors Dmitry Baranchuk, Artem Babenko, Yury Malkov