◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Anna V. Kaluzhnaya

15 papers hereh-index 10436 citations43 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4
  • last author11

Across the 15 of 15 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • cs.NE5
  • stat.ML2
  • cs.AI1
  • cs.OH1
  • physics.ao-ph1

identity via Semantic Scholar / OpenAlex

activity
20182025
most citedAutomated Evolutionary Approach for the Design of Composite Machine Learning Pipelines

80 citations · 183 across the 13 of their papers we have counts for

collaborators
Showing 2021 · cs.LGShow all

3 papers · 2 filters

cs.LG2021★ 80 cited

Automated Evolutionary Approach for the Design of Composite Machine Learning Pipelines

Nikolay O. Nikitin, Pavel Vychuzhanin, Mikhail Sarafanov +6

The effectiveness of the machine learning methods for real-world tasks depends on the proper structure of the modeling pipeline. The proposed approach is aimed to automate the desi…

cs.LG2021★ 39 cited

Hybrid and Automated Machine Learning Approaches for Oil Fields Development: the Case Study of Volve Field, North Sea

Nikolay O. Nikitin, Ilia Revin, Alexander Hvatov +2

The paper describes the usage of intelligent approaches for field development tasks that may assist a decision-making process. We focused on the problem of wells location optimizat…

cs.LG2021

Automated data-driven approach for gap filling in the time series using evolutionary learning

Mikhail Sarafanov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya

In the paper, we propose an adaptive data-driven model-based approach for filling the gaps in time series. The approach is based on the automated evolutionary identification of the…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.