Michael Purrer - Institut fur Theoretische;Universitat Wien

基本信息

Career Trajectory

Bio

My reseach interests include gravitational wave source modeling and data analysis, numerical and statistical methods, and machine learning techniques.

Research Interests

Papers共 59 篇Author StatisticsCo-AuthorSimilar Experts

By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选

Real-time Gravitational-Wave Inference for Binary Neutron Stars Using Machine Learning

Maximilian Dax,Stephen R. Green,Jonathan Gair, Nihar Gupte,Michael Pürrer,Vivien Raymond,Jonas Wildberger, Jakob H. Macke,Alessandra Buonanno, Bernhard Schölkopf

CoRR (2024)

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Evidence for Eccentricity in the Population of Binary Black Holes Observed by LIGO-Virgo-KAGRA

Nihar Gupte,Antoni Ramos-Buades,Alessandra Buonanno,Jonathan Gair,M. Coleman Miller,Maximilian Dax,Stephen R. Green,Michael Pürrer,Jonas Wildberger,Jakob Macke, Isobel M. Romero-Shaw,Bernhard Schölkopf

arxiv（2024）

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Accounting for Numerical-Relativity Calibration Uncertainty in Gravitational-Wave Modeling and Inference

Lorenzo Pompili,Alessandra Buonanno,Michael Pürrer

arxiv（2024）

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Incorporating Waveform Calibration Error in Gravitational-Wave Modeling and Inference for SEOBNRv4

Ritesh Bachhar,Michael Pürrer,Stephen R. Green

arxiv（2024）

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A Fully Precessing Higher-Mode Surrogate Model of Effective-One-body Waveforms

Bhooshan Gadre,Michael Pürrer,Scott E. Field,Serguei Ossokine,Vijay Varma

Physical Review Dno. 12 (2024)

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Adapting to Noise Distribution Shifts in Flow-Based Gravitational-Wave Inference

Jonas Wildberger,Maximilian Dax,Stephen R. Green,Jonathan Gair,Michael Puerrer,Jakob H. Macke,Alessandra Buonanno,Bernhard Schoelkopf

Physical review D/Physical review Dno. 8 (2023)

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Pyseobnr: a Software Package for the Next Generation of Effective-One-body Multipolar Waveform Models

Deyan P. Mihaylov,Serguei Ossokine,Alessandra Buonanno,Hector Estelles,Lorenzo Pompili,Michael Pürrer,Antoni Ramos-Buades

arXiv (Cornell University) (2023)

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Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference

Maximilian Dax,Stephen R. Green,Jonathan Gair,Michael Purrer,Jonas Wildberger,Jakob H. Macke,Alessandra Buonanno,Bernhard Scholkopf

PHYSICAL REVIEW LETTERS（2023）

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Applications of Deep Learning to Physics Workflows

Manan Agarwal,Jay Alameda,Jeroen Audenaert,Will Benoit,Damon Beveridge,Meghna Bhattacharya,Chayan Chatterjee,Deep Chatterjee, Andy Chen, Muhammed Saleem Cholayil, Chia-Jui Chou, Sunil Choudhary,Michael Coughlin,Maximilian Dax, Aman Desai,Andrea Di Luca,Javier Mauricio Duarte,Steven Farrell,Yongbin Feng, Pooyan Goodarzi,Ekaterina Govorkova,Matthew Graham,Jonathan Guiang,Alec Gunny,Weichangfeng Guo,Janina Hakenmueller,Ben Hawks,Shih-Chieh Hsu,Pratik Jawahar,Xiangyang Ju,Erik Katsavounidis,Manolis Kellis,Elham E Khoda, Fatima Zahra Lahbabi, Van Tha Bik Lian,Mia Liu,Konstantin Malanchev,Ethan Marx,William Patrick McCormack,Alistair McLeod,Geoffrey Mo,Eric Anton Moreno,Daniel Muthukrishna,Gautham Narayan, Andrew Naylor,Mark Neubauer,Michael Norman,Rafia Omer,Kevin Pedro,Joshua Peterson,Michael Pürrer,Ryan Raikman, Shivam Raj,George Ricker, Jared Robbins,Batool Safarzadeh Samani,Kate Scholberg,Alex Schuy,Vasileios Skliris,Siddharth Soni,Niharika Sravan,Patrick Sutton,Victoria Ashley Villar, Xiwei Wang,Linqing Wen,Frank Wuerthwein,Tingjun Yang, Shu-Wei Yeh

arXiv (Cornell University) (2023)

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