| druGAN: an advanced generative adversarial autoencoder model for de novo generation of new molecules with desired molecular properties in silico A Kadurin, S Nikolenko, K Khrabrov, A Aliper, A Zhavoronkov Molecular pharmaceutics 14 (9), 3098-3104, 2017 | 506 | 2017 |
| The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology A Kadurin, A Aliper, A Kazennov, P Mamoshina, Q Vanhaelen, ... Oncotarget 8 (7), 10883, 2017 | 363 | 2017 |
| nabladft: Large-scale conformational energy and hamiltonian prediction benchmark and dataset K Khrabrov, I Shenbin, A Ryabov, A Tsypin, A Telepov, A Alekseev, ... Physical Chemistry Chemical Physics 24 (42), 25853-25863, 2022 | 15 | 2022 |
| FREED++: Improving RL Agents for Fragment-Based Molecule Generation by Thorough Reproduction A Telepov, A Tsypin, K Khrabrov, S Yakukhnov, P Strashnov, P Zhilyaev, ... Transactions on Machine Learning Research (TMLR), 2023 | | 2023 |
| Gradual Optimization Learning for Conformational Energy Minimization A Tsypin, L Ugadiarov, K Khrabrov, M Avetisian, A Telepov, E Rumiantsev, ... arXiv preprint arXiv:2311.06295, 2023 | | 2023 |
| The small cage in the Zoo of terminal Fano threefolds. K Khrabrov | | 2014 |
| Chemical Language Models Have Problems with Chemistry: A Case Study on Molecule Captioning Task V Ganeeva, K Khrabrov, A Kadurin, A Savchenko, E Tutubalina The Second Tiny Papers Track at ICLR 2024, 0 | | |
Artur KadurinArtificial Intelligence Research Institute; KubSUVerified email at airi.net
