Experimenting with CNN architectures for image classification and methods to improve training with small datasets (semi-supervised learning).
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Updated
Jul 27, 2018 - Python
Experimenting with CNN architectures for image classification and methods to improve training with small datasets (semi-supervised learning).
Advanced Scheduling Algorithm for Managing Pseudo Labels in Semi-Supervised Learning
PyTorch implementation of Bayesian Graph Convolutional Networks using Neighborhood Random Walk Sampling to supplement my Honors Thesis.
Implementation of Co-training Regressors (COREG) semi-supervised regression algorithm from Zhou and Li, 2005.
Unofficial Pytorch Implementation of 'FixMatch- Simplifying Semi-Supervised Learning with Consistency and Confidence'
A sparsified AutoEncoder to solve Semi-Supervised classification tasks
Exercises from IT3030 V20
Codebase accompanying the paper "Efficient Co-Regularised Least Squares Regression".
Deep Semisupervised Cross-modal Retrieval/Cross-view Recognition (IEEE TCYB 2022, PyTorch Code)
Code for L2ID CVPRW 2021 paper Improving Semi-Supervised Domain Adaptation Using Effective Target Selection and Semantics
The sslearn library is a Python package for machine learning over Semi-supervised datasets. It is an extension of scikit-learn.
Inner product natural graph factorization machine used in 'GEMSEC: Graph Embedding with Self Clustering' .
Source codes for the paper "Local Additivity Based Data Augmentation for Semi-supervised NER"
An alternative implementation of Recursive Feature and Role Extraction (KDD11 & KDD12)
Code for reproducing results in GraphMix paper
An implementation of "Community Preserving Network Embedding" (AAAI 2017)
Reference implementation of Diffusion2Vec (Complenet 2018) built on Gensim and NetworkX.
The TensorFlow reference implementation of 'GEMSEC: Graph Embedding with Self Clustering' (ASONAM 2019).
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