Introduction to graph representation learning, including methods for embedding graph data, graph neural networks, and deep generative models of graphs.

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2020-05-24 · An overview of self-supervised pretext tasks in Natural Language Processing

self-supervised-learning natural-language-processing article representation-learning

2020-06-14 · Introduce a series of effective graph-structured networks, including non-local neural networks, spatial generalized propagation networks, etc.

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2020-04-11 · A self-supervised method to generate labels via simultaneous clustering and representation learning

self-supervised-learning image-clustering computer-vision illustrated

Simple Convolutional Auto-encoder based image similarity search to find similar images to given image or features. Fully written in PyTorch.

image-similarity-search pytorch autoencoders computer-vision

2020-07-20 · A Temporal Extension Library for PyTorch Geometric

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2020-06-19 · A general approach to distill symbolic representations of a learned deep model by introducing strong inductive biases.

symbolic-models inductive-bias graph-neural-networks graphs

2020-08-04 · This project presents a simple framework to retrieve images similar to a query image.

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2020-08-02 · This blog post enlists a few of my favorite recipes in deep learning in the context of computer vision (as of August 2020).

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2020-04-08 · How to load pretrained/finetuned SimCLR models from hub modules for fine-tuning.

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