Neural Density Estimation and Likelihood-free Inference
George Papamakarios : https://arxiv.org/pdf/1910.13233.pdf
#Bayesian #NeuralDensityEstimation #Inference

Introduction to Capsules by Sara Sabour, Google


https://www.youtube.com/watch?v=zRg3IuxaJ6I

https://t.iss.one/ArtificialIntelligenceArticles

Improving Generalization in Meta Reinforcement Learning using Learned Objectives
Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber : https://arxiv.org/abs/1910.04098
#ArtificialIntelligence #MetaReinforcementLearning #ReinforcementLearning

Engineers at Google have unveiled Dex, a prototype functional language designed for array processing. Array processing is a cornerstone of the math used in machine learning applications and other computationally intensive work.

#dex #machinelearning #linearalgebra

https://openreview.net/pdf?id=rJxd7vsWPS

Artificial Intelligence replaces Fashion photographers as it renders photo-realistic images of fashion models wearing outfits from input images of isolated clothing items.

Takes #StyleGAN to the next level.
Great work by zalandoresearch #iccv2019

Read https://arxiv.org/pdf/1908.08847.pdf

interesting.
https://www.biorxiv.org/content/10.1101/787101v2 https://www.youtube.com/watch?time_continue=40&v=nf-P3b2AnZw&fbclid=IwAR3Vtk9MKYPb6KFRIvk3Bgjeedw-i-8th1srJpbNQVHR_KpOzMa-p50RHx0

Improving Generalization in Meta Reinforcement Learning using Learned Objectives
Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber : https://arxiv.org/abs/1910.04098
#ArtificialIntelligence #MetaReinforcementLearning #ReinforcementLearning

NIPS 2017 Invited talk
"Deep Reinforcement Learning with Subgoals"
By David Silver: https://vimeo.com/249557775
#ArtificialIntelligence #DeepLearning #MachineLearning #NeuralNetworks #ReinforcementLearning

PyRoboLearn: A Python Framework for Robot Learning Practitioners

Delhaisse et al.: https://robotlearn.github.io/pyrobolearn/

#ArtificialIntelligence #Python #Robotics

Google PhD Fellowship program is now accepting applications.
Deadline is Dec 1st.

Google PhD Fellowships directly support graduate students as they pursue their PhD, as well as connect them to a Google Research Mentor.


https://ai.google/research/outreach/phd-fellowship/

The lighter side of Reinforcemnent Learning... 😂

"Encouraged to try to touch the ball as many times as it can, the robot develops a strategy of standing next to the ball and rapidly vibrating."

From "Rebooting AI: Building Artificial Intelligence We Can Trust|" by Gary Marcus and Ernest Davis.

https://www.amazon.com/Rebooting-AI-Building-Artificial-Intelligence/dp/1524748250

Adversarial NLI: A New Benchmark for Natural Language Understanding

Nie et al.: https://arxiv.org/abs/1910.14599

#NaturalLanguageUnderstanding #MachineLearning #DeepLearning

Mechanical Engineer
https://aijobs.com/jobs/mechanical-engineer/

https://t.iss.one/ArtificialIntelligenceArticles

What does it mean for a machine to “understand”?
The use of words like “real”, “true”, and “genuine” imply that “understanding” is binary ... I argue that “understanding” exists along a continuous spectrum of capabilities.
In order for a system to understand, it must create linkages between different concepts, states, and actions. Today’s language translation systems correctly link “water” in English to “agua” in Spanish, but they don’t have any links between “water” and “electric shock”.
Seeking a definition of intelligence without including an agent’s environment is like seeking the sound of one hand clapping.
The other motivation of definitions of intelligence is that of Occam’s razor. This is what motivates the idea that compression is equal to intelligence.
Blogs
https://medium.com/@tdietterich/what-does-it-mean-for-a-machine-to-understand-555485f3ad40
https://medium.com/intuitionmachine/how-to-define-intelligence-b9bac630960b