YohanJung

bandlimited-cnns

Band-limited Training and Inference for Convolutional Neural Networks

WaveFlow

A PyTorch implementation of "WaveFlow: A Compact Flow-based Model for Raw Audio" (ICML 2020)

Randomly-Projected-Additive-GPs

Code for Randomly Projected Additive Gaussian Processes

cnn-surrogate

Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification

Bayesian-Neural-Networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

FourierExtraction

This repo contains the source code related to the ICLR submission named: Retrieving Signals in the Frequency Domain with Deep Complex Extractors

TCN

Sequence modeling benchmarks and temporal convolutional networks

deep_complex_networks

Implementation related to the Deep Complex Networks

spectral_representations_for_convolutional_neural_networks

tensorflow-fft-cnn-spectral

differentiableFIVO

Working Folder

VariationalGaussianCopula

Matlab Code for Variational Gaussian Copula Inference

ssl-suite

SSL using PyTorch

mmvae

Multimodal Mixture-of-Experts VAE

adanet

[ICCV 2019 oral] Code for Semi-Supervised Learning by Augmented Distribution Alignment

flowgmm

nn_robust_attacks

Robust evasion attacks against neural network to find adversarial examples

semisup-adv

Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf

pytorch_structure2vec

pytorch implementation of structure2vec (https://arxiv.org/abs/1603.05629)

GPflow-inter-domain

Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables

ladder

Ladder network is a deep learning algorithm that combines supervised and unsupervised learning

ladder_network_keras

Semi-Supervised Learning with Ladder Networks in Keras. Get 98% test accuracy on MNIST with just 100 labeled examples !

Sparse-GP

ibp_vae

mean-field and structured VAEs for the IBP

aigp

The code for the inference method, AIGP, for Gaussian Processes

AAAI2019_DSSL

Code for our AAAI 2019 paper "Distribution-based Semi-Supervised Learning for Activity Recognition".

SVSHGP

Stochastic variational heteroscedastic Gaussian process

pytorch-seq2seq

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

GPCnoise

Implementation of scalable Gaussian process classification (GPC) with additive noise for various likelihoods

CLGP

Categorical Latent Gaussian Process