tearcloud's repositories
awesome-causality-algorithms
An index of algorithms for learning causality with data
awesome-graph-transformer
Papers about graph transformers.
balanced-loss
Easy to use class balanced cross entropy and focal loss implementation for Pytorch
Graphormer
Graphormer is a general-purpose deep learning backbone for molecular modeling.
GTA
Learning Graph Structures with Transformer for Multivariate Time Series Anomaly Detection in IoT
mtad-gat-pytorch
PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).
NLP-Loss-Pytorch
Implementation of some unbalanced loss like focal_loss, dice_loss, DSC Loss, GHM Loss et.al
pyGAT
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
pytorch-deep-learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
TranAD
[VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.