Sepp Hochreiter

E736829

person researcher

Sepp Hochreiter is an Austrian computer scientist best known as a co-inventor of Long Short-Term Memory (LSTM) networks and a pioneer in deep learning and recurrent neural networks.

Try in SPARQL Jump to: Surface forms Statements Referenced by

All labels observed (1)

Label	Occurrences
Sepp Hochreiter canonical	2

Statements (46)

Predicate	Object
instanceOf	person ⓘ researcher ⓘ
academicDegree	PhD in computer science ⓘ
awardReceived	Austrian Cross of Honour for Science and Art NERFINISHED ⓘ J. K. Aggarwal Prize of the International Association for Pattern Recognition NERFINISHED ⓘ
citizenship	Austria ⓘ
coInvented	LSTM NERFINISHED ⓘ Long Short-Term Memory NERFINISHED ⓘ
coInventedWith	Jürgen Schmidhuber NERFINISHED ⓘ
contributedTo	analysis of vanishing gradient problem in recurrent neural networks ⓘ
doctoralAdvisor	Jürgen Schmidhuber NERFINISHED ⓘ
educatedAt	Technische Universität München NERFINISHED ⓘ
employer	Johannes Kepler University Linz NERFINISHED ⓘ
familyName	Hochreiter NERFINISHED ⓘ
fieldOfResearch	gradient-based learning ⓘ sequence learning ⓘ vanishing gradient problem ⓘ
fieldOfWork	artificial intelligence ⓘ computer science ⓘ deep learning ⓘ machine learning ⓘ neural networks ⓘ recurrent neural networks ⓘ
givenName	Sepp NERFINISHED ⓘ
hasAcademicAffiliation	Austrian Academy of Sciences NERFINISHED ⓘ
hasHIndex	high citation impact in machine learning research ⓘ
hasRole	pioneer of deep learning ⓘ pioneer of recurrent neural networks ⓘ
influenced	applications of LSTM in handwriting recognition ⓘ applications of LSTM in natural language processing ⓘ applications of LSTM in speech recognition ⓘ development of modern sequence modeling ⓘ
knownFor	LSTM NERFINISHED ⓘ Long Short-Term Memory NERFINISHED ⓘ deep learning ⓘ recurrent neural networks ⓘ
languageSpoken	German ⓘ
name	Sepp Hochreiter NERFINISHED ⓘ
nationality	Austrian ⓘ
notablePublication	Long Short-Term Memory (1997) NERFINISHED ⓘ
positionHeld	head of Institute for Machine Learning ⓘ professor ⓘ
researchInterest	bioinformatics applications of machine learning ⓘ optimization in deep learning ⓘ probabilistic modeling ⓘ
workInstitution	Johannes Kepler University Linz NERFINISHED ⓘ

Referenced by (2)

Full triples — surface form annotated when it differs from this entity's canonical label.

Alex Graves → influencedBy → Sepp Hochreiter ⓘ

Fréchet Inception Distance → introducedBy → Sepp Hochreiter ⓘ