Ashish Vaswani
E457851
Ashish Vaswani is a computer scientist and machine learning researcher best known as a lead author of the seminal "Attention Is All You Need" paper that introduced the Transformer architecture.
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
artificial intelligence researcher
ⓘ
computer scientist ⓘ machine learning researcher ⓘ |
| academicDegree | PhD in computer science ⓘ |
| areaOfInfluence |
artificial intelligence
ⓘ
computer science ⓘ |
| coAuthorOf | "Attention Is All You Need" NERFINISHED ⓘ |
| coAuthorWith |
Aidan N. Gomez
NERFINISHED
ⓘ
Illia Polosukhin NERFINISHED ⓘ Jakob Uszkoreit NERFINISHED ⓘ Llion Jones NERFINISHED ⓘ Niki Parmar NERFINISHED ⓘ Noam Shazeer NERFINISHED ⓘ Łukasz Kaiser NERFINISHED ⓘ |
| contributedTo | self-attention mechanisms in neural networks ⓘ |
| countryOfCitizenship | India ⓘ |
| developed | Transformer architecture (as part of a team) ⓘ |
| educatedAt |
University of California, San Diego
NERFINISHED
ⓘ
University of Southern California ⓘ |
| employer |
Adept AI Labs
NERFINISHED
ⓘ
Google Brain (past) NERFINISHED ⓘ Google Research (past) NERFINISHED ⓘ |
| fieldOfWork |
deep learning
ⓘ
machine learning ⓘ natural language processing ⓘ neural networks ⓘ |
| gender | male ⓘ |
| hasCitationCount | tens of thousands of citations for "Attention Is All You Need" ⓘ |
| hasRole | lead author of "Attention Is All You Need" ⓘ |
| influenced |
large language models
ⓘ
modern NLP architectures ⓘ sequence-to-sequence modeling ⓘ |
| knownFor |
co-authoring the paper "Attention Is All You Need"
ⓘ
contributing to the Transformer architecture ⓘ |
| languageOfWorkOrName | English ⓘ |
| notableAchievement | helped establish attention-based models as a standard in deep learning ⓘ |
| notableConcept | Transformer model NERFINISHED ⓘ |
| notableWork | "Attention Is All You Need" NERFINISHED ⓘ |
| position | co-founder of Adept AI Labs ⓘ |
| publicationYearOfNotableWork | 2017 ⓘ |
| researchInterest |
attention mechanisms
ⓘ
representation learning ⓘ sequence modeling ⓘ |
| thesisTopic | machine learning ⓘ |
| venueOfNotableWork | NeurIPS 2017 NERFINISHED ⓘ |
| workLocation |
California, United States
ⓘ
surface form:
California
United States of America ⓘ
surface form:
United States
|
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
Łukasz Kaiser