Tamás Budavári

Tamás Budavári

Johns Hopkins University

H-index: 62

North America-United States

About Tamás Budavári

Tamás Budavári, With an exceptional h-index of 62 and a recent h-index of 40 (since 2020), a distinguished researcher at Johns Hopkins University, specializes in the field of applied statistics, computational science, data science, computer science, astronomy.

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

Splines'n Lines: Rest-frame galaxy spectral energy distributions via Bayesian functional data analysis

Fast Globally Optimal Catalog Matching using MIQCP

A flexible Expectation-Maximization framework for fast, scalable and high-fidelity multi-frame astronomical image deconvolution

Learning the Night Sky with Deep Generative Priors

Super-resolution sub-band image reconstruction with prescribed PSF and application to Hyper Suprime-Cam exposures

IVOA Spectrum Data Model Version 1.2

Towards Optimal Line of Sight Coverage

DeepForge for astronomy: Deep learning SDSS redshifts from images

Tamás Budavári Information

University

Position

Dept. of Applied Mathematics and Statistics The

Citations(all)

43238

Citations(since 2020)

9058

Cited By

37678

hIndex(all)

62

hIndex(since 2020)

40

i10Index(all)

123

i10Index(since 2020)

72

Email

University Profile Page

Johns Hopkins University

Google Scholar

View Google Scholar Profile

Tamás Budavári Skills & Research Interests

applied statistics

computational science

data science

computer science

astronomy

Top articles of Tamás Budavári

Title

Journal

Author(s)

Publication Date

Splines'n Lines: Rest-frame galaxy spectral energy distributions via Bayesian functional data analysis

arXiv preprint arXiv:2310.19340

David Kent

Tamás Budavári

Thomas J Loredo

David Ruppert

2023/10/30

Fast Globally Optimal Catalog Matching using MIQCP

The Astronomical Journal

Jacob Feitelberg

Amitabh Basu

Tamás Budavári

2023/9/27

A flexible Expectation-Maximization framework for fast, scalable and high-fidelity multi-frame astronomical image deconvolution

arXiv preprint arXiv:2302.05804

Yashil Sukurdeep

Fausto Navarro

Tamas Budavari

2023/2/11

Learning the Night Sky with Deep Generative Priors

arXiv preprint arXiv:2302.02030

Fausto Navarro

Daniel Hall

Tamas Budavari

Yashil Sukurdeep

2023/2/3

Super-resolution sub-band image reconstruction with prescribed PSF and application to Hyper Suprime-Cam exposures

American Astronomical Society Meeting Abstracts

Yashil Sukurdeep

Fausto Navarro

Tamas Budavari

2023/1

IVOA Spectrum Data Model Version 1.2

IVOA Recommendation 15 December 2023

Mark Cresitello-Dittmar

Jonathan McDowell

Doug Tody

Tamas Budavari

Markus Dolensky

...

2023/12

Towards Optimal Line of Sight Coverage

Peter Gu

Tamás Budavári

Amanda Galante

Randal Burns

2022/10/11

DeepForge for astronomy: Deep learning SDSS redshifts from images

Astronomy and Computing

Umesh Timalsina

Brian Broll

Kyle Moore

Tamás Budavári

Ákos Lédeczi

2022/7/1

Globally optimal and scalable N-way matching of astronomy catalogs

The Astronomical Journal

Tu Nguyen

Amitabh Basu

Tamás Budavári

2022/5/30

Probabilistic association of transients to their hosts (PATH)

The Astrophysical Journal

Kshitij Aggarwal

Tamás Budavári

Adam T Deller

Tarraneh Eftekhari

Clancy W James

...

2021/4/20

Combinatorial optimization for urban planning: strategic demolition of abandoned houses in Baltimore, MD

Journal of Planning Education and Research

Philip ME Garboden

Chi-Wen Fan

Tamás Budavári

Amitabh Basu

Michael Braverman

...

2021/4/8

Wireless sensor network for in situ soil moisture monitoring

arXiv preprint arXiv:2102.10260

Jianing Fang

Chuheng Hu

Nour Smaoui

Doug Carlson

Jayant Gupchup

...

2021/2/20

Photometric redshifts via Bayesian functional data analysis

American Astronomical Society Meeting Abstracts

T Loredo

T Budavari

D Kent

D Ruppert

2021/1

GPU-Accelerated Hierarchical Bayesian Inference with Application to Modeling Cosmic Populations: CUDAHM

arXiv preprint arXiv:2105.08026

János M Szalai-Gindl

Thomas J Loredo

Brandon C Kelly

István Csabai

Tamás Budavári

...

2021/5/17

CUDAHM: MCMC sampling of hierarchical models with GPUs

Astrophysics Source Code Library

JM Szalai-Gindl

TJ Loredo

BC Kelly

I Csabai

T Budavári

...

2021/5

Optimal probabilistic catalogue matching for radio sources

Monthly Notices of the Royal Astronomical Society

Dongwei Fan

Tamás Budavári

Ray P Norris

Amitabh Basu

2020/10/11

A machine learning gateway for scientific workflow design

Scientific Programming

Brian Broll

Umesh Timalsina

Péter Völgyesi

Tamás Budavári

Ákos Lédeczi

...

2020/9/29

Computational tools for the spectroscopic analysis of white dwarfs

Monthly Notices of the Royal Astronomical Society

Vedant Chandra

Hsiang-Chih Hwang

Nadia L Zakamska

Tamás Budavári

2020/9

wdtools: Spectroscopic analysis of white dwarfs

Astrophysics Source Code Library

Vedant Chandra

Hsiang-Chih Hwang

Nadia L Zakamska

Tamás Budavári

2020/7

A User-friendly Environmental Sensor Platform for Monitoring Soil Systems

AGU Fall Meeting Abstracts

Jianing Fang

Nour Smaoui

Doug Carlson

Katalin A Szlavecz

Alexander Szalay

...

2020/12

See List of Professors in Tamás Budavári University(Johns Hopkins University)

Co-Authors

H-index: 166
Timothy Heckman

Timothy Heckman

Johns Hopkins University

H-index: 127
Max Tegmark

Max Tegmark

Massachusetts Institute of Technology

H-index: 127
Prof. Karl Glazebrook

Prof. Karl Glazebrook

Swinburne University of Technology

H-index: 125
Neta Bahcall

Neta Bahcall

Princeton University

H-index: 123
Gordon Richards

Gordon Richards

Drexel University

H-index: 123
A. S. Szalay

A. S. Szalay

Johns Hopkins University

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