PHYRE: A New Benchmark for Physical Reasoning
By: Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson and Ross Girshick. Facebook AI Research : https://research.fb.com/publications/phyre-a-new-benchmark-for-physical-reasoning/
Demo: https://player.phyre.ai
#DeepLearning #Physics #ReinforcementLearning

Does the brain do backpropagation? CAN Public Lecture - Geoffrey Hinton

One of the best recent talks of Prof. geoffrey hinton
online on computation in the brain. Intriguingly, the proposed relation between the neuron firing rate and the error signal looks quite similar to the Euler-Lagrange equation of motion in Physics.

https://www.youtube.com/watch?v=qIEfJ6OBGj8

@ArtificialIntelligenceArticles

Visualizing and Measuring the Geometry of BERT
Coenen et al.: https://arxiv.org/abs/1906.02715
#BERT #NaturalLanguageProcessing #UnsupervisedLearning

An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents

Such et al.: https://arxiv.org/abs/1812.07069

Code: https://github.com/uber-research/atari-model-zoo

Blog: https://eng.uber.com/atari-zoo-deep-reinforcement-learning/

#ArtificialIntelligence #DeepLearning #ReinforcementLearning

Deep Kernel Learning for Clustering
Wu et al.: https://arxiv.org/pdf/1908.03515v1.pdf
#DeepLearning #MachineLearning #NeuralNetworks

"One-shot Face Reenactment"
Zhang et al.: https://arxiv.org/abs/1908.03251
Project: https://wywu.github.io/projects/ReenactGAN/OneShotReenact.html
GitHub: https://github.com/bj80heyue/One_Shot_Face_Reenactment
#ArtificialIntelligence #DeepLearning #MachineLearning

Creative improvisation is at the root of jazz and science.

https://www.openculture.com/2016/07/the-secret-link-between-jazz-and-physics-how-einstein-coltrane-shared-improvisation-and-intuition-in-common.html

Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real
Nachum et al.: https://arxiv.org/abs/1908.05224
#Robotics #ArtificialIntelligence #MachineLearning

Something really really cool!🙂
#weekend_read
Paper-Title: Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real #GoogleAI
Link to the paper: https://arxiv.org/pdf/1908.05224.pdf
Link to the videos: https://sites.google.com/view/manipulation-via-locomotion
TL;DR: They have presented successful zero-shot transfer of policies trained in simulation to perform difficult locomotion and manipulation via locomotion tasks. The key to their method is the imposition of hierarchy, which introduces modularity into the domain randomization process and enables the learning of increasingly complex behaviours.

Best Resources for Getting Started With GANs
https://machinelearningmastery.com/resources-for-getting-started-with-generative-adversarial-networks/

Pytorch Implementation of Autoregressive Language Model
https://github.com/lyeoni/pretraining-for-language-understanding

Unconstrained Monotonic Neural Networks

Antoine Wehenkel and Gilles Louppe : https://arxiv.org/abs/1908.05164

#NeuralNetworks #MachineLearning #NeuralComputing

12 NLP Researchers, Practitioners & Innovators You Should Be Following
Check out this list of NLP researchers, practitioners and innovators you should be following, including academics, practitioners, developers, entrepreneurs, and more.
https://www.kdnuggets.com/2019/08/nlp-researchers-practitioners-innovators-should-follow.html

Conditional Neural Processes
Garnelo et al.: https://arxiv.org/abs/1807.01613
1. Repo: https://github.com/deepmind/neural-processes
2. NoteBook: https://github.com/deepmind/neural-processes/blob/master/conditional_neural_process.ipynb
#ArtificialIntelligence #MachineLearning

A guide to convolution arithmetic for deep learning
Vincent Dumoulin and Francesco Visin : https://arxiv.org/pdf/1603.07285.pdf
#artificialintelligence #deeplearning #machinelearning

CS231n Convolutional Neural Networks for Visual Recognition

https://cs231n.github.io/neural-networks-3/#loss

Sports Matches & Artificial Intelligence
https://www.youtube.com/watch?v=kaslJ-8piSE&feature=youtu.be

Gitflow - Using git in a right way

https://sharetechlinks.com/post/detail/89/gitflow-using-git-in-a-right-way

Does Deep Learning Still Need Backpropagation?
https://syncedreview.com/2019/08/14/does-deep-learning-still-need-backpropagation/

Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems. https://arxiv.org/abs/1908.05480

Automated Rib Fracture Detection of Postmortem Computed Tomography Images Using Machine Learning Techniques
https://arxiv.org/abs/1908.05467