Michael P Brenner
Michael is an applied mathematician, interested in the interface between machine learning and science.
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Authored Publications
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Neural general circulation models for weather and climate
Dmitrii Kochkov
Janni Yuval
Ian Langmore
Jamie Smith
Griffin Mooers
Milan Kloewer
James Lottes
Peter Dueben
Samuel Hatfield
Peter Battaglia
Alvaro Sanchez
Matthew Willson
Nature, 632 (2024), pp. 1060-1066
Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns
Ariel Goldstein
Avigail Grinstein-Dabush
Haocheng Wang
Zhuoqiao Hong
Bobbi Aubrey
Samuel A. Nastase
Zaid Zada
Eric Ham
Harshvardhan Gazula
Eliav Buchnik
Werner Doyle
Sasha Devore
Patricia Dugan
Roi Reichart
Daniel Friedman
Orrin Devinsky
Adeen Flinker
Uri Hasson
Nature Communications (2024)
Using large language models to accelerate communication for eye gaze typing users with ALS
Subhashini Venugopalan
Katie Seaver
Xiang Xiao
Katrin Tomanek
Sri Jalasutram
Ajit Narayanan
Bob MacDonald
Emily Kornman
Daniel Vance
Blair Casey
Steve Gleason
(2024)
Speech Intelligibility Classifiers from 550k Disordered Speech Samples
Katie Seaver
Richard Cave
Neil Zeghidour
Rus Heywood
Jordan Green
ICASSP, Icassp submission. 2022 (2023)
A Machine-Learning Based Objective Measure for ALS disease progression
Fernando Viera
Alan S Premasiri
Maeve McNally
Steven Perrin
npj Digital Medicine (2022)
Context-Aware Abbreviation Expansion Using Large Language Models
Katrin Tomanek
Ajit Narayanan
Annual Conference of the North American Chapter of the Association for Computational Linguistics, 2022 (2022) (to appear)
COVID-19 Open-Data: a global-scale spatially granular meta-dataset for coronavirus disease
Oscar Wahltinez
Aurora Cheung
Ruth Alcantara
Donny Cheung
Anthony Erlinger
Matt Lee
Pranali Yawalkar
Paula Lê
Ofir Picazo Navarro
Scientific Data (2022)
Shared computational principles for language processing in humans and deep language models
Ariel Goldstein
Zaid Zada
Eliav Buchnik
Amy Price
Bobbi Aubrey
Samuel A. Nastase
Harshvardhan Gazula
Gina Choe
Aditi Rao
Catherine Kim
Colton Casto
Lora Fanda
Werner Doyle
Daniel Friedman
Patricia Dugan
Lucia Melloni
Roi Reichart
Sasha Devore
Adeen Flinker
Liat Hasenfratz
Omer Levy,
Kenneth A. Norman
Orrin Devinsky
Uri Hasson
Nature Neuroscience (2022)
Comparing Supervised Models And Learned Speech Representations For Classifying Intelligibility Of Disordered Speech On Selected Phrases
Joel Shor
Katrin Tomanek
Jordan R. Green
Interspeech, Interspeech 2021 (2021) (to appear)
Machine learning accelerated computational fluid dynamics
Ayya Alieva
Dmitrii Kochkov
Jamie Alexander Smith
Proceedings of the National Academy of Sciences USA (2021)
