YouTube UGC Dataset for Video Compression Research. https://arxiv.org/abs/1904.06457

Patch redundancy in images: a statistical testing framework and some applications. https://arxiv.org/abs/1904.06428

Towards Accurate One-Stage Object Detection with AP-Loss. https://arxiv.org/abs/1904.06373

The iWildCam 2018 Challenge Dataset. https://arxiv.org/abs/1904.05986

Best Paper Awards in Computer Science (since 1996)

A well maintained list: https://jeffhuang.com/best_paper_awards.html

#artificialintelligence #award #machinelearning #papers #research @ArtificialIntelligenceArticles

Disney trying to automate making an animation
https://arxiv.org/pdf/1904.05440.pdf

Visualizing Attention in Transformer-Based Language Representation Models
Jesse Vig: https://arxiv.org/abs/1904.02679
#ArtificialIntelligence #MachineLearning #NaturalLanguageProcessing

Natural Language Semantics With Pictures: Some Language & Vision Datasets and Potential U... https://arxiv.org/abs/1904.07318

A Realistic Dataset and Baseline Temporal Model for Early Drowsiness Detection. https://arxiv.org/abs/1904.07312

Brain Tumor Segmentation on MRI with Missing Modalities. https://arxiv.org/abs/1904.07290

entureBeat article on the singing voice conversion system developed at FAIR-Tel Aviv.
This can transform someone's singing voice into someone else's voice

https://venturebeat.com/2019/04/16/facebooks-ai-can-convert-one-singers-voice-into-another/

Ian Goodfellow: Generative Adversarial Networks (GANs)
@ArtificialIntelligenceArticles
This conversation with Ian led me to rethink the way I see several basic ideas in deep learning, including generative models, adversarial learning, and reasoning. I definitely enjoyed it and hope you do as well.



https://www.youtube.com/watch?v=Z6rxFNMGdn0&fbclid=IwAR1P-iKyeed3-8GziQp59ZxPBkHZ9yX1fK1slAUK1MIbQJPK7cy0exDzTQ8

https://t.iss.one/ArtificialIntelligenceArticles

Standards for AI Governance: International Standards to Enable Global Coordination in AI Research & Development
By Peter Cihon,Research Affiliate, Center for the Governance of AI Future of Humanity Institute, University of Oxford: https://www.fhi.ox.ac.uk/wp-content/uploads/Standards_-FHI-Technical-Report.pdf
#ArtificialIntelligence

Datasheets for Datasets

https://arxiv.org/abs/1803.09010
#Databases #ArtificialIntelligence #AIEthics #Ethics #MachineLearning

80 Best Data Science Books That Are Worthy Reading
https://www.octoparse.com/blog/80-best-data-science-books-that-are-worthy-reading

Advanced Machine Learning: Neural Architecture Search

A great lecture by Debadeepta Dey from Microsoft Research:
https://www.youtube.com/watch?v=wL-p5cjDG64

Neural Painters: A learned differentiable constraint for generating brushstroke paintings
By Reiichiro Nakano https://arxiv.org/abs/1904.08410
GitHub: https://github.com/reiinakano/neural-painters/tree/master/notebooks
Colab notebooks: https://colab.research.google.com/github/reiinakano/neural-painters/

4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks
Choy et al.: https://arxiv.org/abs/1904.08755
#ArtificialIntelligence #DeepLearning #NeuralNetworks

Single Cortical Neurons as Deep Artificial Neural Networks
Beniaguev et al.: https://www.biorxiv.org/content/biorxiv/early/2019/04/18/613141.full.pdf
#DeepLearning #MachineLearning #SynapticIntegration

A List Of Top 10 Deep Learning Papers, The 2018 Edition https://www.techleer.com/articles/517-a-list-of-top-10-deep-learning-papers-the-2018-edition/

Deep Learning State of the Art (2019) by lex fridman
https://youtu.be/53YvP6gdD7U @ArtificialIntelligenceArticles