IEEE

Multi-Task Learning for Video Processing: Going With the Flow

Abstract: Multi-task learning constitutes the prevalent paradigm in numerous vision applications that cast an eye on runtime efficiency. At present however, deep multi-task networks are limited in ...
GitHub

Language Guided Concept Bottleneck Models for Interpretable Continual Learning

This repo is the official PyTorch implementation of CVPR2025 paper "Language Guided Concept Bottleneck Models for Interpretable Continual Learning". We follow the framework of Pilot to implement this ...
GitHub

Learn PyTorch for Deep Learning

Welcome to the Zero to Mastery Learn PyTorch for Deep Learning course, the second best place to learn PyTorch on the internet (the first being the PyTorch documentation). 00 - PyTorch Fundamentals ...
IEEE

Clustered Federated Multi-Task Learning: A Communication-and-Computation Efficient Sparse Sharing Approach

Abstract: Federated multi-task learning (FMTL) is a promising technology to tackle one of the most severe non-independent and identically distributed (non-IID) data challenge in federated learning (FL ...