most citedAn explanation method for Siamese neural networks

5 citations · 10 across the 4 of their papers we have counts for

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5 papers

cs.LG20201 cited

Counterfactual explanation of machine learning survival models

Maxim S. Kovalev, Lev V. Utkin

A method for counterfactual explanation of machine learning survival models is proposed. One of the difficulties of solving the counterfactual explanation problem is that the class…

cs.LG20204 cited

SurvLIME-Inf: A simplified modification of SurvLIME for explanation of machine learning survival models

Lev V. Utkin, Maxim S. Kovalev, Ernest M. Kasimov

A new modification of the explanation method SurvLIME called SurvLIME-Inf for explaining machine learning survival models is proposed. The basic idea behind SurvLIME as well as Sur…

cs.LG2020

A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds

Maxim S. Kovalev, Lev V. Utkin

A new robust algorithm based of the explanation method SurvLIME called SurvLIME-KS is proposed for explaining machine learning survival models. The algorithm is developed to ensure…

cs.LG2020

SurvLIME: A method for explaining machine learning survival models

Maxim S. Kovalev, Lev V. Utkin, Ernest M. Kasimov

A new method called SurvLIME for explaining machine learning survival models is proposed. It can be viewed as an extension or modification of the well-known method LIME. The main i…

cs.LG20195 cited

An explanation method for Siamese neural networks

Lev V. Utkin, Maxim S. Kovalev, Ernest M. Kasimov

A new method for explaining the Siamese neural network is proposed. It uses the following main ideas. First, the explained feature vector is compared with the prototype of the corr…