avmoldovan

CNN-TE

ACM-GNN-forked

NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN framework

AE_ts

Auto encoder for time series

AHLC

Our paper is accepted by IJCNN 2021----Automatic CNN Compression Based on Hyper-parameter Learning

Automatic_Speech_Recognition

End-to-end automatic speech recognition from scratch in Tensorflow

Bidirectional-Deep-readout-Echo-State-Network

Heterophily_and_oversmoothing-forked

Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"

CycleGAN

Software that generates photos from paintings, turns horses into zebras, performs style transfer, and more (from UC Berkeley)

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

DeepLearningImplementations

Implementation of recent Deep Learning papers

Echo-State-Network-with-Intrinsic-Plasticity

A MATLAB implementation of an Echo State Network, using an unsupervised learning rule for pre-training the reservoir called Intrinsic Plasticity.

evolution-strategies-starter

Starter code for Evolution Strategies

GAN-Sandbox

Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.

GAT-forked

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

gcn

Implementation of Graph Convolutional Networks in TensorFlow

GCNII-forked

PyTorch implementation of "Simple and Deep Graph Convolutional Networks"

generative-adversarial-networks

Introduction to generative adversarial networks, with code to accompany the O'Reilly tutorial on GANs

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

HiGCN-forked

HOG-GCN-forked

improved_wgan_training

Code for reproducing experiments in "Improved Training of Wasserstein GANs"

keras

Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.

LSTM-TimeSeries-tutorial

TimeSeries using LSTM tutorial

nn-from-scratch

Implementing a Neural Network from Scratch

powerful-gnns-forked

How Powerful are Graph Neural Networks?

pygcn-forked

Graph Convolutional Networks in PyTorch

Savitzky-Golay

Computes the Savitzky-Golay Filter coefficients

ssp-forked

TensorFlow_TimeSeries_RNN_MapR

TensorFlow code from my blog post https://mapr.com/blog/deep-learning-tensorflow/

WassersteinGAN