activity
20172021
most citedA Predictive Model for Steady-State Multiphase Pipe Flow: Machine Learning on Lab Data

103 citations · 169 across the 13 of their papers we have counts for

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10 papers · 1 filter

cs.LG2021

Data-driven model for hydraulic fracturing design optimization. Part II: Inverse problem

Viktor Duplyakov, Anton Morozov, Dmitriy Popkov +5

We describe a stacked model for predicting the cumulative fluid production for an oil well with a multistage-fracture completion based on a combination of Ridge Regression and CatB…

cs.LG2021

Adversarial Attacks on Deep Models for Financial Transaction Records

Ivan Fursov, Matvey Morozov, Nina Kaploukhaya +7

Machine learning models using transaction records as inputs are popular among financial institutions. The most efficient models use deep-learning architectures similar to those in…

cs.LG2021

COHORTNEY: Non-Parametric Clustering of Event Sequences

Vladislav Zhuzhel, Rodrigo Rivera-Castro, Nina Kaploukhaya +3

Cohort analysis is a pervasive activity in web analytics. One divides users into groups according to specific criteria and tracks their behavior over time. Despite its extensive us…

cs.LG20203 cited

Topology-based Clusterwise Regression for User Segmentation and Demand Forecasting

Rodrigo Rivera-Castro, Aleksandr Pletnev, Polina Pilyugina +4

Topological Data Analysis (TDA) is a recent approach to analyze data sets from the perspective of their topological structure. Its use for time series data has been limited. In thi…

cs.LG20204 cited

Differentiable Language Model Adversarial Attacks on Categorical Sequence Classifiers

I. Fursov, A. Zaytsev, N. Kluchnikov +2

An adversarial attack paradigm explores various scenarios for the vulnerability of deep learning models: minor changes of the input can force a model failure. Most of the state of…

cs.LG2020

Data-driven models and computational tools for neurolinguistics: a language technology perspective

Ekaterina Artemova, Amir Bakarov, Aleksey Artemov +2

In this paper, our focus is the connection and influence of language technologies on the research in neurolinguistics. We present a review of brain imaging-based neurolinguistic st…