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asap

AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

be_great

A novel approach for synthesizing tabular data using pretrained large language models

common-code

illustrated-machine-learning.github.io

Website containing illustrations about Machine Learning theory!

keras-unet-collection

The Tensorflow, Keras implementation of U-net, V-net, U-net++, UNET 3+, Attention U-net, R2U-net, ResUnet-a, U^2-Net, TransUNET, and Swin-UNET with optional ImageNet-trained backbones.

machine-learning-notes

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接

mambaout

MambaOut: Do We Really Need Mamba for Vision?

multi-glau

pypots

A Python toolbox/library for reality-centric machine/deep learning and data mining on partially-observed time series with PyTorch, including SOTA neural network models for science tasks of imputation, classification, clustering, and forecasting on incomplete (irregularly-sampled) multivariate time series with NaN missing values/data.

pytorch-deep-learning

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

pytorch-gat

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

retinal-fundus-classification-using-xai-and-segmentation