Search Results for author:
Found 6 papers, 6 papers with code
DUCK: Distance-based Unlearning via Centroid Kinematics
Machine Unlearning is rising as a new field, driven by the pressing necessity of ensuring privacy in modern artificial intelligence models.
Predicting Tweet Engagement with Graph Neural Networks
Social Networks represent one of the most important online sources to share content across a world-scale audience.
Exemplar-free Continual Learning of Vision Transformers via Gated Class-Attention and Cascaded Feature Drift Compensation
Secondly, we propose a new method of feature drift compensation that accommodates feature drift in the backbone when learning new tasks.
Explaining Image Enhancement Black-Box Methods through a Path Planning Based Algorithm
In this paper we present a path planning algorithm which provides a step-by-step explanation of the output produced by state of the art enhancement methods, overcoming black-box limitation.
Offset equivariant networks and their applications
In this paper we present a framework for the design and implementation of offset equivariant networks, that is, neural networks that preserve in their output uniform increments in the input.
TreEnhance: A Tree Search Method For Low-Light Image Enhancement
Given as input a low-light image, TreEnhance produces as output its enhanced version together with the sequence of image editing operations used to obtain it.
Ranked #1 on
Image Enhancement
on MIT-Adobe FiveK
