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Rajat Kumar Sarkar

3 papers here

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

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • physics.flu-dyn1
ORCID 0009-0003-3900-7381

identity via Semantic Scholar / OpenAlex

most citedHypergraph Learning based Recommender System for Anomaly Detection, Control and Optimization

6 citations · 7 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2024★ 6 cited

Hypergraph Learning based Recommender System for Anomaly Detection, Control and Optimization

Sakhinana Sagar Srinivas, Rajat Kumar Sarkar, Venkataramana Runkana

Anomaly detection is fundamental yet, challenging problem with practical applications in industry. The current approaches neglect the higher-order dependencies within the networks…

cs.LG2024★ 1 cited

Vision HgNN: An Electron-Micrograph is Worth Hypergraph of Hypernodes

Sakhinana Sagar Srinivas, Rajat Kumar Sarkar, Sreeja Gangasani +1

Material characterization using electron micrographs is a crucial but challenging task with applications in various fields, such as semiconductors, quantum materials, batteries, et…

physics.flu-dyn2024

PointSAGE: Mesh-independent superresolution approach to fluid flow predictions

Rajat Sarkar, Krishna Sai Sudhir Aripirala, Vishal Sudam Jadhav +2

Computational Fluid Dynamics (CFD) serves as a powerful tool for simulating fluid flow across diverse industries. High-resolution CFD simulations offer valuable insights into fluid…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.