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Pytorch implementation for the paper: Data augmentation with norm-AE and selective pseudo-labelling for unsupervised domain adaptation
MemAE for anomaly detection. -- Gong, Dong, et al. "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection". ICCV 2019.
A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
Variational Autoencoders trained on the SVHN and FashionMNIST data-sets implemented in PyTorch
A Tensorflow implementation of paper, Deep CORAL: Correlation Alignment for Deep Domain Adaptation
Implementation of Hinton's dropout to Convolution Neural Networks
Graph Neural Networks with Keras and Tensorflow 2.
Harmonization of multi-site imaging data with ComBat (Python)
Harmonizing neuroimaging data across scanners and sites
scikit-learn cross validators for iterative stratification of multilabel data
Mastering TensorFlow 1x, published by Packt
Semi-Supervised Fine-Grained Recognition Challenge at FGVC7
Website with general information about AOMIC
Code for the paper "VAE with a VampPrior", J.M. Tomczak & M. Welling
Common curation/preprocessing/qc scripts for AOMIC
ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping
Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as PyTensor: www.github.…
Deep Learning Tutorial notes and code. See the wiki for more info.
Code release for Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation (ICML 2019)
A collection of AWESOME things about domian adaptation