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researcher

A. Phan

9 papers hereh-index 277.6k citations141 works total

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

author position
  • first author3
  • middle author2
  • last author4

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.CV2
  • math.NA2
  • eess.SP1
  • math.OC1
same name
  • A. Phan — 53 papers
  • A. Phan — 16 papers, h 59
  • A. Phan — 2 papers
  • A. Phan — 1 paper, h 45
  • A. Phan — 1 paper, h 59
  • A. Phan — 1 paper, h 9

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

activity
20162025
most citedMachine learning models for DOTA 2 outcomes prediction

16 citations · 28 across the 7 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.CV2020★ 2 cited

Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network

Anh-Huy Phan, Konstantin Sobolev, Konstantin Sozykin +6

Most state of the art deep neural networks are overparameterized and exhibit a high computational cost. A straightforward approach to this problem is to replace convolutional kerne…

eess.SP2020★ 4 cited

Graph Convolutional Neural Networks for analysis of EEG signals, BCI application

Mirfarid Musavian Ghazani, Anh Huy Phan

Decoding brain signals has gained many attention and has found much applications in recent years such as Brain Computer Interfaces, communicating with controlling external devices…

cs.CV2020★ 5 cited

CNN Acceleration by Low-rank Approximation with Quantized Factors

Nikolay Kozyrskiy, Anh-Huy Phan

The modern convolutional neural networks although achieve great results in solving complex computer vision tasks still cannot be effectively used in mobile and embedded devices due…

cs.LG2020

Deep convolutional tensor network

Philip Blagoveschensky, Anh Huy Phan

Neural networks have achieved state of the art results in many areas, supposedly due to parameter sharing, locality, and depth. Tensor networks (TNs) are linear algebraic represent…

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