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researcher

M. T. Young

4 papers here

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.CV1
  • q-bio.BM1

identity via Semantic Scholar / OpenAlex

most citedExascale Deep Learning for Scientific Inverse Problems

30 citations · 31 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2020

Computer-aided abnormality detection in chest radiographs in a clinical setting via domain-adaptation

Abhishek K Dubey, Michael T Young, Christopher Stanley +2

Deep learning (DL) models are being deployed at medical centers to aid radiologists for diagnosis of lung conditions from chest radiographs. Such models are often trained on a larg…

cs.LG2020★ 1 cited

Towards the Development of Entropy-Based Anomaly Detection in an Astrophysics Simulation

Drew Schmidt, Bronson Messer, M. Todd Young +1

The use of AI and ML for scientific applications is currently a very exciting and dynamic field. Much of this excitement for HPC has focused on ML applications whose analysis and c…

cs.LG2019★ 30 cited

Exascale Deep Learning for Scientific Inverse Problems

Nouamane Laanait, Joshua Romero, Junqi Yin +6

We introduce novel communication strategies in synchronous distributed Deep Learning consisting of decentralized gradient reduction orchestration and computational graph-aware grou…

q-bio.BM2019

Deep Generative Model Driven Protein Folding Simulation

Heng Ma, Debsindhu Bhowmik, Hyungro Lee +4

Significant progress in computer hardware and software have enabled molecular dynamics (MD) simulations to model complex biological phenomena such as protein folding. However, enab…

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