MOMA: A Multi-task Attention Learning Algorithm for Multi-omics Data Interpretation and Classification

The PyTorch implementation for multi-task attention guided network (MTAGN) in End to End Multi-task learning with Attention for Multi-objective Fault Diagnosis under Small Sample

Attention-based multi-task learning for speech-enhancement and speaker-identification in multi-speak

This repository contains the implementation of the method proposed in 'End-To-End Multi-Task Learning with Attention' by Liu et al. 2019, for the Deep Learning final exam.

Multi-task Attention-based Semi-supervised Learning framework for image segmentation

multi-task learning for text recognition with joint CTC-attention

Bachelor's thesis: Using LSTMs, CNNs and multi-task learning to predict 3D protein structure.

PyTorch implementation of multi-task learning architectures, incl. MTI-Net (ECCV2020).

The implementation of "End-to-End Multi-Task Learning with Attention" [CVPR 2019].