Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Kirpichenko, Stanislav R."'
A method for solving concept-based learning (CBL) problem is proposed. The main idea behind the method is to divide each concept-annotated image into patches, to transform the patches into embeddings by using an autoencoder, and to cluster the embedd
Externí odkaz:
http://arxiv.org/abs/2406.19897
A new model for generating survival trajectories and data based on applying an autoencoder of a specific structure is proposed. It solves three tasks. First, it provides predictions in the form of the expected event time and the survival function for
Externí odkaz:
http://arxiv.org/abs/2402.12331
A new approach to the local and global explanation is proposed. It is based on selecting a convex hull constructed for the finite number of points around an explained instance. The convex hull allows us to consider a dual representation of instances
Externí odkaz:
http://arxiv.org/abs/2401.16294
A method for estimating the conditional average treatment effect under condition of censored time-to-event data called BENK (the Beran Estimator with Neural Kernels) is proposed. The main idea behind the method is to apply the Beran estimator for est
Externí odkaz:
http://arxiv.org/abs/2211.10793
A new method for estimating the conditional average treatment effect is proposed in the paper. It is called TNW-CATE (the Trainable Nadaraya-Watson regression for CATE) and based on the assumption that the number of controls is rather large whereas t
Externí odkaz:
http://arxiv.org/abs/2207.09139
Autor:
Konstantinov, Andrei V., Utkin, Lev V., Kirpichenko, Stanislav R., Kozlov, Boris V., Ageev, Andrey Y.
Publikováno v:
In Procedia Computer Science 2022 212:454-463
Publikováno v:
Progress in Artificial Intelligence (2192-6352); Sep2023, Vol. 12 Issue 3, p257-273, 17p