Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

Code and data used to conduct an empirical analysis of regularised multi-task learning methods.

This repository contains data analysis scripts that I have used for my Master thesis research on multi-fidelity Bayesian optimization. The origin of the raw experimental data can be found in the thesis (not in this repository).

Multi-species clustering of HiC data (Fotuhi Siahpirani et al, Genome Biology 2016)

Multitask Learning Resources

Source code for the paper "VOGUE: Answer Verbalization through Multi Task Learning"

Totana

the web page for my master research

Project for Advanced Audio Processing Course at Tampere University

SWMH dataset extended with sentiment labels and 8 emotion labels

A (hopefully) relatively straightforward, easy to modify code base for running a variety of multi-task optimization setups, with a focus on gradient aggregation methods and model analysis.

The goal is to fit a curve to data, also known as curve fitting, We have to make a model to learn a network that does not learn a single function but a family of functions.

Work based on the latest prompt learning paradigm with LLMs

This is the official code repository for the ACL Findings Paper "Multi-Task Transfer Matters During Instruction-Tuning"

Implementation of the COGP model

This repository includes a multi-task learning example on the face images to classify the genders and races of people. The dataset is from the Kaggle.

Clustered Multi-layer Federated Learning with Rough Estimators.

Participants in this Specialization have the opportunity to construct and train various neural network architectures, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Transformers. They learn to enhance these networks with techniques such as Dropout, BatchNorm, Xavier/He initialization, among others.

Multi-Label, Multi-Task Deep Learning Approach Towards Detection The Differences Between Real And Fake Emotions