"Anyone Can Learn Artificial Intelligence With This Blog"

A Simple, Illustrated Explanation in Colab, By David Code : https://colab.research.google.com/drive/1VdwQq8JJsonfT4SV0pfXKZ1vsoNvvxcH

#artificialintelligence #deeplearning #neuralnetworks

FairSight: Visual Analytics for Fairness in Decision Making. arxiv.org/abs/1908.00176

Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation. arxiv.org/abs/1908.00169

Supervised Learning of the Global Risk Network Activation from Media Event Reports. arxiv.org/abs/1908.00164

Multi-path Learning for Object Pose Estimation Across Domains. arxiv.org/abs/1908.00151

3D Virtual Garment Modeling from RGB Images. arxiv.org/abs/1908.00114

Energy-Based Adversarial Training and Video Prediction, NeurIPS 2016

By Yann LeCun, Facebook AI Research

YouTube: https://youtu.be/x4sI5qO6O2Y

#DeepLearning #EnergyBasedModels #UnsupervisedLearning

Deep TabNine: The all-language autocompleter.

It uses machine learning to provide responsive, reliable, and relevant suggestions.
Traditional autocompleters suggest one word at a time while Deep TabNine, based on GPT-2 and trained on 22 million Github files suggest way much more.

Isn't it cool ! Give it a try 🙌

Website: https://tabnine.com/
Github: https://github.com/zxqfl/tabnine

"Advanced NLP with spaCy"
By Ines Montani : https://course.spacy.io
#machinelearning #nlp #naturallanguageprocessing

"Rapid research framework for PyTorch. The researcher's version of Keras"

GitHub, by William Falcon : https://github.com/williamFalcon/pytorch-lightning

#deeplearning #pytorch #research

Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview

Jiawei Zhang : https://arxiv.org/abs/1908.00187

#MachineLearning #NeuralEvolutionary #MachineLearning

Functional Regularisation for Continual Learning
Titsias et al.: https://arxiv.org/abs/1901.11356
#ArtificialIntelligence #BayesianInference #MachineLearning

Disentangling Disentanglement in Variational Autoencoders

Mathieu et al.: https://proceedings.mlr.press/v97/mathieu19a.html

#DeepLearning #VariationalAutoencoders #VAE

MelNet: A Generative Model for Audio in the Frequency Domain

Sean Vasquez, Mike Lewis: https://arxiv.org/abs/1906.01083

Blog: https://sjvasquez.github.io/blog/melnet/

#ArtificialIntelligence #AudioProcessing #MachineLearning

Welcome this Chinese DeepLearning Chip called “Tianjic”.

Paper: https://www.nature.com/articles/s41586-019-1424-8

It can run traditional deep learning code and also perform "neuromorophic" operations in the same circuitry.

Ten trends in Deep learning NLP
https://blog.floydhub.com/ten-trends-in-deep-learning-nlp/

"Deep Boltzmann Machines"
Ruslan Salakhutdinov and Geoffrey Hinton : https://proceedings.mlr.press/v5/salakhutdinov09a/salakhutdinov09a.pdf
#BoltzmannMachines #DeepBoltzmannMachines #DeepLearning

CS231N: Convolutional Neural Networks for Visual Recognition

Stanford University School of Engineering : https://www.youtube.com/playlist?list=PLzUTmXVwsnXod6WNdg57Yc3zFx_f-RYsq

#ArtificialIntelligence #MachineLearning #NeuralNetworks