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Artem Babenko
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Towards Real-time Text-driven Image Manipulation with Unconditional Diffusion Models


Apr 10, 2023
Nikita Starodubcev, Dmitry Baranchuk, Valentin Khrulkov, Artem Babenko

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Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts


Feb 27, 2023
Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova

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A critical look at the evaluation of GNNs under heterophily: are we really making progress?


Feb 22, 2023
Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova

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Is This Loss Informative? Speeding Up Textual Inversion with Deterministic Objective Evaluation


Feb 09, 2023
Anton Voronov, Mikhail Khoroshikh, Artem Babenko, Max Ryabinin

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* Code: https://github.com/yandex-research/DVAR. 12 pages, 11 figures 
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TabDDPM: Modelling Tabular Data with Diffusion Models


Sep 30, 2022
Akim Kotelnikov, Dmitry Baranchuk, Ivan Rubachev, Artem Babenko

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* code https://github.com/rotot0/tab-ddpm 
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Characterizing Graph Datasets for Node Classification: Beyond Homophily-Heterophily Dichotomy


Sep 13, 2022
Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova

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Revisiting Pretraining Objectives for Tabular Deep Learning


Jul 12, 2022
Ivan Rubachev, Artem Alekberov, Yury Gorishniy, Artem Babenko

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* Code: https://github.com/puhsu/tabular-dl-pretrain-objectives 
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Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor Search


May 08, 2022
Harsha Vardhan Simhadri, George Williams, Martin Aumüller, Matthijs Douze, Artem Babenko, Dmitry Baranchuk, Qi Chen, Lucas Hosseini, Ravishankar Krishnaswamy, Gopal Srinivasa, Suhas Jayaram Subramanya, Jingdong Wang

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On Embeddings for Numerical Features in Tabular Deep Learning


Mar 15, 2022
Yury Gorishniy, Ivan Rubachev, Artem Babenko

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* Code: https://github.com/Yura52/tabular-dl-num-embeddings (v2: minor fixes) 
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