Joan Bruna
E473813
Joan Bruna is a mathematician and computer scientist known for his foundational work in theoretical deep learning, including convolutional architectures and scattering networks.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Joan Bruna canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4833509 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joan Bruna Context triple: [Intriguing properties of neural networks, author, Joan Bruna]
-
A.
Miquel Barceló
Miquel Barceló is a renowned contemporary Spanish painter and sculptor known for his experimental techniques and large-scale works, including major public art commissions.
-
B.
Montserrat Ribé
Montserrat Ribé is a Spanish makeup and special effects artist best known for her work on Guillermo del Toro’s films, including the creature designs in "Pan’s Labyrinth."
-
C.
Bernat Vilaplana
Bernat Vilaplana is a Spanish film editor known for his frequent collaborations with director Guillermo del Toro on acclaimed films such as Pan’s Labyrinth.
-
D.
Enric Sagnier
Enric Sagnier was a prolific Catalan architect whose eclectic yet prominently Modernisme-influenced works helped shape the urban landscape of Barcelona in the late 19th and early 20th centuries.
-
E.
Adrià Puigdomènech Badia
Adrià Puigdomènech Badia is a researcher and contributor in the field of computer science, known for work related to the A3C (Asynchronous Advantage Actor-Critic) reinforcement learning algorithm.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Joan Bruna Target entity description: Joan Bruna is a mathematician and computer scientist known for his foundational work in theoretical deep learning, including convolutional architectures and scattering networks.
-
A.
Miquel Barceló
Miquel Barceló is a renowned contemporary Spanish painter and sculptor known for his experimental techniques and large-scale works, including major public art commissions.
-
B.
Montserrat Ribé
Montserrat Ribé is a Spanish makeup and special effects artist best known for her work on Guillermo del Toro’s films, including the creature designs in "Pan’s Labyrinth."
-
C.
Bernat Vilaplana
Bernat Vilaplana is a Spanish film editor known for his frequent collaborations with director Guillermo del Toro on acclaimed films such as Pan’s Labyrinth.
-
D.
Enric Sagnier
Enric Sagnier was a prolific Catalan architect whose eclectic yet prominently Modernisme-influenced works helped shape the urban landscape of Barcelona in the late 19th and early 20th centuries.
-
E.
Adrià Puigdomènech Badia
Adrià Puigdomènech Badia is a researcher and contributor in the field of computer science, known for work related to the A3C (Asynchronous Advantage Actor-Critic) reinforcement learning algorithm.
- F. None of above. chosen
Statements (44)
| Predicate | Object |
|---|---|
| instanceOf |
computer scientist
ⓘ
mathematician ⓘ person ⓘ |
| academicDegree | PhD in applied mathematics ⓘ |
| coAuthorWith |
Arthur Szlam
ⓘ
Stéphane Mallat ⓘ Xavier Bresson ⓘ Yann LeCun ⓘ |
| doctoralAdvisor | Stéphane Mallat ⓘ |
| educatedAt |
Universitat Politècnica de Catalunya
ⓘ
linked to:
Polytechnic University of Catalonia
École Normale Supérieure ⓘ
linked to:
École Normale (Paris)
École Polytechnique Fédérale de Lausanne ⓘ
linked to:
École polytechnique fédérale de Lausanne
|
| employer | New York University ⓘ |
| fieldOfWork |
applied mathematics
ⓘ
deep learning ⓘ harmonic analysis ⓘ machine learning ⓘ signal processing ⓘ theoretical deep learning ⓘ |
| hasCitizenship | Spain ⓘ |
| hasRole |
researcher
ⓘ
university professor ⓘ |
| knownFor |
convolutional architectures
ⓘ
invariance and stability in deep representations ⓘ scattering networks ⓘ theoretical analysis of deep neural networks ⓘ wavelet scattering transform ⓘ |
| languageSpoken |
Catalan
ⓘ
English ⓘ French ⓘ Spanish ⓘ |
| notableWork |
Invariant Scattering Convolution Networks
ⓘ
Spectral Networks and Locally Connected Networks on Graphs ⓘ |
| positionHeld |
associate professor at New York University
ⓘ
faculty member at Courant Institute of Mathematical Sciences ⓘ faculty member at NYU Center for Data Science ⓘ |
| researchInterest |
convolutional neural networks
ⓘ
graph neural networks ⓘ high-dimensional statistics ⓘ optimization in deep learning ⓘ representation learning ⓘ theory of neural networks ⓘ |
| workInstitution |
Center for Data Science, New York University
ⓘ
Courant Institute of Mathematical Sciences ⓘ
linked to:
New York University
|
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Joan Bruna Description of subject: Joan Bruna is a mathematician and computer scientist known for his foundational work in theoretical deep learning, including convolutional architectures and scattering networks.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.