Understanding Deep Neural Networks Through the Lens of their Non-Linearity
Séminaire Palaisien, ENSAE, Paris, France
| CARVIEW |
Select Language
HTTP/2 301
server: GitHub.com
content-type: text/html
location: https://qbouniot.github.io/talks/
access-control-allow-origin: *
strict-transport-security: max-age=31556952
expires: Wed, 31 Dec 2025 00:09:25 GMT
cache-control: max-age=600
x-proxy-cache: MISS
x-github-request-id: B1A2:2118F1:A7CC04:BCCF9A:6954675C
accept-ranges: bytes
age: 0
date: Tue, 30 Dec 2025 23:59:25 GMT
via: 1.1 varnish
x-served-by: cache-bom-vanm7210034-BOM
x-cache: MISS
x-cache-hits: 0
x-timer: S1767139165.408260,VS0,VE219
vary: Accept-Encoding
x-fastly-request-id: 287b323f7302f856a620f6336a139b5784749558
content-length: 162
HTTP/2 200
server: GitHub.com
content-type: text/html; charset=utf-8
last-modified: Fri, 03 Oct 2025 13:22:19 GMT
access-control-allow-origin: *
strict-transport-security: max-age=31556952
etag: W/"68dfce0b-4a4b"
expires: Wed, 31 Dec 2025 00:09:25 GMT
cache-control: max-age=600
content-encoding: gzip
x-proxy-cache: MISS
x-github-request-id: CA74:444BC:A99CC6:BE9E27:6954675D
accept-ranges: bytes
age: 0
date: Tue, 30 Dec 2025 23:59:25 GMT
via: 1.1 varnish
x-served-by: cache-bom-vanm7210034-BOM
x-cache: MISS
x-cache-hits: 0
x-timer: S1767139166.640447,VS0,VE218
vary: Accept-Encoding
x-fastly-request-id: 0c9f56f7e2f3fbc7752356305fd7a14070a21c48
content-length: 5432
Talks and presentations - Quentin Bouniot 
Quentin Bouniot
Post-Doctoral Researcher at TUM and Helmholtz Munich
- Munich, Germany
- Github
- Google Scholar
Talks and presentations
On Few-Annotation Learning and Non-Linearity in Deep Neural Networks
February 06, 2024
Séminaire, CMAP, Paris, France
Improving Few-Shot Learning through Multi-task Representation Learning Theory
November 26, 2021
National Research Group Talk, Vers un apprentissage pragmatique dans un contexte de données visuelles labellisées limitées; GdR ISIS, Paris, France
Vers une meilleure compréhension des méthodes de méta-apprentissage à travers la théorie de l’apprentissage de représentations multi-tâches
June 14, 2021
National Conference Talk, Conférence sur l'Apprentissage Automatique (CAp) 2021, Saint-Étienne, France
Optimal Transport as a Defense Against Adversarial Attacks
May 26, 2021
Conference Talk, International Conference on Pattern Recognition (ICPR) 2020, Virtual
Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms
December 11, 2020
Conference Workshop talk, NeurIPS 2020 Workshop on Meta-Learning (MetaLearn 2020), Virtual
Vulnerability of Person Re-Identification Models to Metric Adversarial Attacks
September 23, 2020
Talk, DATAIA Workshop « Safety & AI » 2020, CentraleSupélec, Université Paris-Saclay, France
Vulnerability of Person Re-Identification Models to Metric Adversarial Attacks
June 19, 2020
Conference Workshop, CVPR 2020 Workshop on Adversarial Machine Learning in Computer Vision, Virtual