How AI Reshapes Inverse Problems in Imaging
Pierre WEISS
PhD, CNRS Researcher, CBI – CNRS
March 14th, 2024
Abstract
Inverse problems consist in reconstructing signals from incomplete information.
Computational Protein Design with Automated Reasoning and Deep Learning
Marianne DEFRESNE
PhD, AI Scientist at Torus AI
February 8th, 2024
Abstract
Proteins are complex molecules that perform many functions
A Brain-Inspired Reinforcement Learning Mechanism for Pattern Recognition
Milad MOZAFARI
PhD, Research Scientist at Torus AI
November 23rd, 2023
Abstract
The reinforcement learning (RL) mechanism in the mammalian
Main Challenges for Machine Learning in Critical Systems
Grégory FLANDIN
PhD, Program Director at IRT Saint Exupéry
November 9th, 2023
Abstract
Recent progress in Artificial Intelligence, especially in
Statistical Modeling and Analysis of Radio-Induced Adverse Effects Based on In Vitro Data
Polina ARSENTEVA
PhD Student, Université de Bourgogne
October 26th, 2023, 4 PM
Abstract
This talk addresses the problem of adverse
Machine Learning in Satellite Imagery
Valentina DISARLO
PhD, Postdoct at Universitaet Heidelberg
September 28th, 2023, 4 PM
Abstract
Satellite and aerial imagery are potent tools
Gradient Strikes Back: How Filtering Out High Frequencies Improves Explanations
Sabine MUZELLEC
PhD Student, CerCo – CNRS, Toulouse
September 14th, 2023, 4 PM
Recent years have witnessed an explosion in the
Advancing Antibiotic Resistance Classification with Deep Learning Using Protein Sequence and Structure
Aymen QABEL
LIX, École Polytechnique, Palaiseau, France
April 6th, 2023
Abstract
Background: Antibiotic resistance is a major global health concern,
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
