Thomas Merkh

About Thomas Merkh

Thomas Merkh, With an exceptional h-index of 5 and a recent h-index of 5 (since 2020), a distinguished researcher at University of California, Los Angeles, specializes in the field of Reinforcement Learning, Neural Networks.

His recent articles reflect a diverse array of research interests and contributions to the field:

Experimental benchmarking of an automated deterministic error-suppression workflow for quantum algorithms

Geometry of linear convolutional networks

Automatic Infectious Disease Classification Analysis with Concept Discovery

Improving the performance of algorithms on NISQ-Devices through automated control design and implementation

Experimental deep reinforcement learning for error-robust gate-set design on a superconducting quantum computer

Semi-supervised nonnegative matrix factorization for document classification

Semi-supervised nmf models for topic modeling in learning tasks

Thomas Merkh Information

University

Position

___

Citations(all)

143

Citations(since 2020)

129

Cited By

20

hIndex(all)

5

hIndex(since 2020)

5

i10Index(all)

4

i10Index(since 2020)

4

Email

University Profile Page

Google Scholar

Thomas Merkh Skills & Research Interests

Reinforcement Learning

Neural Networks

Top articles of Thomas Merkh

Experimental benchmarking of an automated deterministic error-suppression workflow for quantum algorithms

Physical Review Applied

2023/8/14

Geometry of linear convolutional networks

SIAM Journal on Applied Algebra and Geometry

2022

Kathlén Kohn
Kathlén Kohn

H-Index: 6

Thomas Merkh
Thomas Merkh

H-Index: 2

Automatic Infectious Disease Classification Analysis with Concept Discovery

arXiv preprint arXiv:2209.02415

2022/8/28

Improving the performance of algorithms on NISQ-Devices through automated control design and implementation

APS March Meeting Abstracts

2022

Experimental deep reinforcement learning for error-robust gate-set design on a superconducting quantum computer

PRX Quantum

2021/11

Semi-supervised nonnegative matrix factorization for document classification

Infection, Genetics and Evolution

2012/7/1

Semi-supervised nmf models for topic modeling in learning tasks

arXiv preprint arXiv:2010.07956

2020/10/15

See List of Professors in Thomas Merkh University(University of California, Los Angeles)