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Shivam Sharma

New Jersey Institute of Technology

4 papers hereh-index 5179 citations10 works total

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

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CL1
  • q-fin.PR1
affiliations
  • New Jersey Institute of Technology
same name
  • Shivam Sharma — 14 papers, h 14
  • Shivam Sharma — 4 papers, h 3
  • Shivam Sharma — 3 papers, h 3
  • Shivam Sharma — 3 papers, h 4
  • Shivam Sharma — 2 papers, h 6
  • Shivam Sharma — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedQuantum-Inspired Tensor Neural Networks for Partial Differential Equations

4 citations · 8 across the 4 of their papers we have counts for

collaborators

4 papers

q-fin.PR2022★ 4 cited

Quantum-Inspired Tensor Neural Networks for Option Pricing

Raj G. Patel, Chia-Wei Hsing, Serkan Sahin +12

Recent advances in deep learning have enabled us to address the curse of dimensionality (COD) by solving problems in higher dimensions. A subset of such approaches of addressing th…

cs.LG2022★ 4 cited

Quantum-Inspired Tensor Neural Networks for Partial Differential Equations

Raj Patel, Chia-Wei Hsing, Serkan Sahin +11

Partial Differential Equations (PDEs) are used to model a variety of dynamical systems in science and engineering. Recent advances in deep learning have enabled us to solve them in…

cs.LG2022

mulEEG: A Multi-View Representation Learning on EEG Signals

Vamsi Kumar, Likith Reddy, Shivam Kumar Sharma +4

Modeling effective representations using multiple views that positively influence each other is challenging, and the existing methods perform poorly on Electroencephalogram (EEG) s…

cs.CL2018

Attentive Recurrent Tensor Model for Community Question Answering

Gaurav Bhatt, Shivam Sharma, Balasubramanian Raman

A major challenge to the problem of community question answering is the lexical and semantic gap between the sentence representations. Some solutions to minimize this gap includes…

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