Graph Contrastive Learning Permalink
An overview of “Deep Graph Contrastive Representation Learning”
An overview of “Deep Graph Contrastive Representation Learning”
brief overview of the Mixture Model Networks (MoNet) architecture
brief overview of the Graph Attention Networks architecture
brief overview of the Residual Gated Graph Convolutional Network architecture
A brief overview of GraphSAGE
A brief overview of Graph Isomorphism Networks (GIN)
A beginner friendly introduction to Convolutional Graph Neural Networks (GCNs).
A beginner friendly introduction to Attention based Graphical Neural Networks (GATs).
A beginner friendly introduction to Message Passing Graph Neural Networks (MPGNNs).
An in-depth breakdown of “Graph Neural Networks with Learnable Structural and Positional Representations” by Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laur...
In the past few months there have been various papers proposing MLP based architectures without Attention or Convolutions. This report analyses the paper ‘ML...
In the past few months there have been various papers proposing MLP based architectures without Attention or Convolutions. This report analyses the paper ‘Re...
It’s no news that transformers have dominated the field of deep learning ever since 2017. But in their recent work, titled ‘Pay Attention to MLPs,’ Hanxiao L...
Continuing on the recent series of reports analyzing newly proposed pure MLP based architectures. In this report I breakdown “FNet Mixing Tokens with Fourier...
An overview of Adaptive Budget Allocation for Parameter Efficient Fine-Tuning
An overview of (QLoRA) Efficient Finetuning of Quantized LLMs
An overview of Intrinsic Dimensions and how they enable Low-Rank Domain Adaptation (LoRA)
An overview of “Low-Rank Adaptation of Large Language Models”
An overview of Intrinsic Dimensions and how they enable Low-Rank Domain Adaptation (LoRA)
A simple end-to-end training and evaluation pipeline in JAX, Flax and Optax.
Learn how to create a simple image classification model in Flax in this short tutorial complete with code and interactive visualizations.
An overview of “Deep Graph Contrastive Representation Learning”
Breakdown of Emerging Properties in Self-Supervised Vision Transformers by Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojan...
A brief overview of Graph Isomorphism Networks (GIN)
An in-depth breakdown of “Graph Neural Networks with Learnable Structural and Positional Representations” by Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laur...
brief overview of the Residual Gated Graph Convolutional Network architecture
A brief overview of GraphSAGE
brief overview of the Mixture Model Networks (MoNet) architecture
brief overview of the Graph Attention Networks architecture