Supervised end-to-end neural architecture that learns how to disambiguate words inside a text.
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Updated
Mar 24, 2023 - Python
Supervised end-to-end neural architecture that learns how to disambiguate words inside a text.
The code of the LFDeep project
Master project on Renal Classification based on MRI images.
ScalableML final project, replicating the paper "Learning General Purpose Distributed Sentence Representations via Large Scale Multitask Learning."
MTLA - Multi-Task Learning Archive
Supplementary material for the paper "Lightweight Multitask Learning for Robust JND Prediction using Latent Space and Reconstructed Frames", IEEE TCSVT, 2024.
yNet: A Breast Ultrasound Image Classification Algorithm Based on Metric Learning
Repo for "Zemi: Learning Zero-Shot Semi-Parametric Language Models from Multiple Tasks" ACL 2023 Findings
A multifactorial optimization paradigm for linkage tree genetic algorithm (Information Science)
Scaleable multitask Network
Rockfall and earthquake detection and association via multitask learning and transfer learning
A boosting procedure for multitask learning on graph-structured data
Named entity recognition for Clinical records. Using MultiHead-Bert + CRF
Structured Multi-task Learning for Molecular Property Prediction, AISTATS'22 (https://proceedings.mlr.press/v151/liu22e.html)
Tensorflow implementation of three architectures for multi-task learning, a paradigm to learn different prediction tasks jointly using one model
repo for practicing DL/genAI
Detection of cerebral microbleeds using deep learning method consisting of 2 steps: initial candidate detection and candidate discrimination using a student-teacher network.
A simple implementation of the paper "Multitask Spectral Learning of Weighted Automata" by Rabusseau et al.
Named Entity Recognition (NER) system trained using a multitask approach
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