IEEE

Multi-Task Reinforcement Learning-Based Multiple Access for Dynamic Wireless Networks

Abstract: With the rapid development of emergent applications, wireless networks require the provision of high throughput. Meanwhile, wireless scenarios exhibit highly dynamic characteristics, ...
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 ...