◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

A. Majumdar

73 papers hereh-index 416.3k citations408 works total

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

author position
  • sole author24
  • first author3
  • middle author8
  • last author38

Across the 73 of 73 papers where every author was matched, so the position is known.

fields
  • cs.LG17
  • cs.CV13
  • eess.SP8
  • eess.IV7
  • cs.AI5
  • cs.CC5
same name
  • A. Majumdar — 105 papers, h 54
  • A. Majumdar — 50 papers, h 19
  • A. Majumdar — 14 papers, h 6
  • A. Majumdar — 13 papers, h 10
  • A. Majumdar — 10 papers, h 110
  • A. Majumdar — 7 papers, h 31

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
20132026
most citedHierarchical Representation Learning for Kinship Verification

81 citations · 168 across the 67 of their papers we have counts for

collaborators
Showing 2015Show all

4 papers · 1 filter

cs.CV2015

Fast Acquisition for Quantitative MRI Maps: Sparse Recovery from Non-linear Measurements

Anupriya Gogna, Angshul Majumdar

This work addresses the problem of estimating proton density and T1 maps from two partially sampled K-space scans such that the total acquisition time remains approximately the sam…

cs.IT2015

Analysis and Synthesis Prior Greedy Algorithms for Non-linear Sparse Recovery

Kavya Gupta, Ankita Raj, Angshul Majumdar

In this work we address the problem of recovering sparse solutions to non linear inverse problems. We look at two variants of the basic problem, the synthesis prior problem when th…

cs.IR2015★ 3 cited

Blind Compressive Sensing Framework for Collaborative Filtering

Anupriya Gogna, Angshul Majumdar

Existing works based on latent factor models have focused on representing the rating matrix as a product of user and item latent factor matrices, both being dense. Latent (factor)…

cs.CV2015★ 13 cited

Real-time Dynamic MRI Reconstruction using Stacked Denoising Autoencoder

Angshul Majumdar

In this work we address the problem of real-time dynamic MRI reconstruction. There are a handful of studies on this topic; these techniques are either based on compressed sensing o…

◍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.