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Online Network Source Optimization with Graph-Kernel MAB
Laura Toni, Pascal Frossard
We propose Grab-UCB, a graph-kernel multi-arms bandit algorithm to learn online the optimal source placement in large scale networks, such that the reward obtained from a priori un…
DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications
Adam Ivankay, Mattia Rigotti, Pascal Frossard
Along with the successful deployment of deep neural networks in several application domains, the need to unravel the black-box nature of these networks has seen a significant incre…
Flexible Channel Dimensions for Differentiable Architecture Search
Ahmet Caner Yüzügüler, Nikolaos Dimitriadis, Pascal Frossard
Finding optimal channel dimensions (i.e., the number of filters in DNN layers) is essential to design DNNs that perform well under computational resource constraints. Recent work i…
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models
Guillermo Ortiz-Jimenez, Alessandro Favero, Pascal Frossard
Task arithmetic has recently emerged as a cost-effective and scalable approach to edit pre-trained models directly in weight space: By adding the fine-tuned weights of different ta…
SequeL: A Continual Learning Library in PyTorch and JAX
Nikolaos Dimitriadis, Francois Fleuret, Pascal Frossard
Continual Learning is an important and challenging problem in machine learning, where models must adapt to a continuous stream of new data without forgetting previously acquired kn…
MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation
Clement Vignac, Nagham Osman, Laura Toni +1
This work introduces MiDi, a novel diffusion model for jointly generating molecular graphs and their corresponding 3D arrangement of atoms. Unlike existing methods that rely on pre…