Equivariant Neural Networks Based on Moving Frames
Mateus SANGALLI
Postdoc, ARMINES, Paris, France
March 23rd, 2023
Abstract
Moving frames are a classical method of obtaining invariants to
Spiking Neural Networks
Timothée MASQUELIER
CNRS Researcher (DR2), Cerco (CNRS)
February 23rd, 2023
Abstract
My main line of research is the study of
A Learning-Based Scheme for Channel Allocation to Vehicular Users in Wireless Networks
Nga NGUYEN
Torus AI, Toulouse, France
February 23rd, 2023
Abstract
Resource allocation algorithms in wireless networks can require solving complex
End-to-end Deep Learning Optimization of a Compressive Spectral Video Camera
Kareth LEON
Postdoc, Université de Toulouse, INP‑IRIT‑ENSEEIHT
April 6th, 2023
Abstract
Spectral videos (which include multispectral and hyperspectral
A Journey Through a Kaggle Competition
Nga NGUYEN
PhD, Torus AI, Toulouse
April 20th, 2023
Abstract
I will present our journey through the Salt segmentation competition
Physics-Constrained Gaussian Process Regression
Iain HENDERSON
PhD, INSA, Toulouse
April 20th, 2023
Abstract
Gaussian process regression (GPR) is a flexible regression method especially suited
How to Use AI for Learning Sign Language in Real Time?
Elisa CABANA
PhD, Post-Doc Researcher, IMDEA Networks, Spain
June 8th, 2023
Abstract
The objective of this project is to develop
Robust Homography Estimation from Local Affine Maps
Mariano RODRIGUEZ
PhD, Machine Learning Engineer at Gladia
June 8th, 2023
Abstract
The corresponding point coordinates determined by classic image
Training Adaptive Reconstruction Networks for Blind Inverse Problems
Alban GOSSARD
Senior Computer Vision Engineer at GoPro
June 22nd, 2023
Abstract
Neural networks allow solving many ill-posed inverse problems
Functional Principal Component Analysis
Frédéric PROTIN
Mathematician, Torus AI, PhD
July 6th, 2023
Abstract
Functional PCA is a generalization of the PCA method of
