Graph Wavelet Neural Network (ICLR 2019) -- Pytorch implementation
Paper: https://openreview.net/forum?id=H1ewdiR5tQ

PyTorch: https://github.com/benedekrozemberczki/GraphWaveletNeuralNetwork

News Feature: What are the limits of deep learning?

https://www.pnas.org/content/116/4/1074

#artificialintelligence #deeplearning #machinelearning

Evolving Neural Networks

https://nn.cs.utexas.edu/downloads/slides/miikkulainen.ijcnn13.pdf

Natural Questions: a New Corpus and Challenge for Question Answering Research

https://ai.googleblog.com/2019/01/natural-questions-new-corpus-and.html

https://t.iss.one/ArtificialIntelligenceArticles

Where is AI heading next? Our study of 25 years of artificial-intelligence research suggests the era of deep learning is coming to an end.
https://www.technologyreview.com/s/612768/we-analyzed-16625-papers-to-figure-out-where-ai-is-headed-next/

Deep Face Recognition: A Survey


https://arxiv.org/abs/1804.06655

https://t.iss.one/ArtificialIntelligenceArticles

Arxiv NLP papers with Github link
https://www.kaggle.com/shujian/arxiv-nlp-papers-with-github-link

New course.
Practical Deep Learning for Coders 2019
https://www.fast.ai/2019/01/24/course-v3/

It's Google’s alternative to the neural network.
https://www.technologyreview.com/the-download/609297/google-researchers-have-a-new-alternative-to-traditional-neural-networks/

Review articles

This is a mostly auto-generated list of review articles on machine learning and artificial intelligence that are on arXiv. Although some of them were written for a specific technical audience or application, the techniques described are nonetheless generally relevant. The list is sorted reverse chronologically. It was generated on 2019-01-24. It includes articles mainly from the arXiv categories cs.AI, cs.CL, cs.CV, cs.IR, cs.LG, cs.NE, eess.IV, and stat.ML. A rememberable short link to this page is https://j.mp/ml-reviews. The source code along with raw data for generating this page are linked. This page is currently not automatically updated.

https://freenode-machinelearning.github.io/Resources/ArticlesReview.html#papers

https://t.iss.one/ArtificialIntelligenceArticles

Berkeley STAT-157 (Introduction to Deep Learning)

Lecture videos for the first week, by Alex Smola: https://www.youtube.com/playlist?list=PLZSO_6-bSqHQHBCoGaObUljoXAyyqhpFW

#artificialneuralnetworks #deeplearning #neuralnetworks

The best of GAN papers in the year 2018

https://dtransposed.github.io/blog/Best-of-GANs-2018-(Part-2-out-of-2).html

https://t.iss.one/ArtificialIntelligenceArticles

The State of AI in 2019

https://www.theverge.com/2019/1/28/18197520/ai-artificial-intelligence-machine-learning-computational-science

A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs

Paper https://arxiv.org/abs/1901.00945

#Neurons #Cognition #MachineLearning

IBM Research Releases ‘Diversity in Faces’ Dataset to Advance Study of Fairness in Facial Recognition Systems

Blog by John R. Smith: https://www.ibm.com/blogs/research/2019/01/diversity-in-faces/

What are Symbolic and Imperative APIs in TensorFlow 2.0?

https://medium.com/tensorflow/what-are-symbolic-and-imperative-apis-in-tensorflow-2-0-dfccecb01021

FaceForensics++: Learning to Detect Manipulated Facial Images

Paper by Rössler et al.: https://arxiv.org/abs/1901.08971

Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning

Paper by Nicolas Papernot, Patrick McDaniel: https://arxiv.org/abs/1803.04765

Code: https://github.com/tensorflow/cleverhans/tree/master/cleverhans/model_zoo/deep_k_nearest_neighbors

VeGANs

A library to easily train various existing GANs (Generative Adversarial Networks) in PyTorch: https://github.com/unit8co/vegans

#pytorch #GAN #GenerativeAdversarialNetworks #MachineLearning

Amazing Machine Learning Open Source of the Year (v.2019)
https://medium.mybridge.co/amazing-machine-learning-open-source-tools-projects-of-the-year-v-2019-95d772e4e985