A Neural Network for Detailed Human Depth Estimation from a Single Image. https://arxiv.org/abs/1910.01275

Linking artificial and human neural representations of language. https://arxiv.org/abs/1910.01244

Cardiac Segmentation of LGE MRI with Noisy Labels. https://arxiv.org/abs/1910.01242

OpenVSLAM: A Versatile Visual SLAM Framework. https://arxiv.org/abs/1910.01122

Unsupervised Pose Flow Learning for Pose Guided Synthesis
Zheng et al.: https://arxiv.org/abs/1909.13819
#ArtificialIntelligence #DeepLearning #MachineLearning https://t.iss.one/ArtificialIntelligenceArticles

Awesome Machine Learning

A curated list of awesome machine learning frameworks, libraries and software (by language).

libraries: https://github.com/josephmisiti/awesome-machine-learning

books: https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md

Gerat book

@ArtificialIntelligenceArticles

Deep learning pioneer Yoshua Bengio explains why and how AI is not magic.

Learn More: https://www.forbes.com/sites/gilpress/2019/09/20/deep-learning-pioneer-yoshua-bengio-says-ai-is-not-magic-and-intel-ai-experts-explain-why-and-how/

Deep Reinforcement Learning

CS 294-112 at UC Berkeley | Instructor Sergey Levine

Lecture Slides : https://rail.eecs.berkeley.edu/deeprlcourse/

#artificialintelligence #deeplearning #reinforcementlearning

Deep Multi-Agent Reinforcement Learning
Jakob N. Foerster : https://ora.ox.ac.uk/objects/uuid:a55621b3-53c0-4e1b-ad1c-92438b57ffa4
#MultiAgent #ReinforcementLearning #DeepLearning

AI & Architecture
An Experimental Perspective

By Stanislas Chaillou, Harvard Graduate School of Design: https://towardsdatascience.com/ai-architecture-f9d78c6958e0

#artificialintelligence #architecture #design #deeplearning #technology

Visualizing the Loss Landscape of Neural Nets

PyTorch code by Tom Goldstein: https://github.com/tomgoldstein/loss-landscape

#pytorch #neuralnetworks #machinelearning #deeplearning #artificialintelligence

Paper by Li Fei-Fei

Causal Induction from Visual Observations for Goal Directed Tasks

https://arxiv.org/abs/1910.01751

#MachineLearning #DeepLearning #ArtificialIntelligence

Population dynamics of synthetic terraformation motifs
Solé et al.: https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.180121
#SyntheticBiology #TheoreticalBiology #Mathematics

On Universal Approximation by Neural Networks with Uniform Guarantees on Approximation of Infinite Dimensional Maps
William H. Guss and Ruslan Salakhutdinov : https://arxiv.org/abs/1910.01545
#ArtificialIntelligence #FunctionalAnalysis #MachineLearning

Benchmarking Batch Deep Reinforcement Learning Algorithms
Fujimoto et al.: https://arxiv.org/abs/1910.01708
#MachineLearning #ArtificialIntelligence #ReinforcementLearning

To counteract phantom limbs, this work employs sensors and actuators, virtual reality and augmented reality, and deep learning to generate missing or dysfunctional limbs.

https://www.profillic.com/paper/arxiv:1910.01191

This awesome story for medical image processing from ETH Zürich #AI researchers needs to be told!

They used #artificialintelligence to improve quality of images recorded by a relatively new biomedical imaging method.

This paves the way towards more accurate #diagnosis and cost-effective devices.

How awesome is that!

Important note on optoacoustic tomography
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They used #machinelearning method to improve optoacoustic imaging. This relatively young #medicalimaging technique can be used for applications such as visualizing blood vessels, studying brain activity, characterizing skin lesions and diagnosing breast cancer.

Paper is here: https://www.nature.com/articles/s42256-019-0095-3
Code: https://github.com/ndavoudi/sparse_artefact_unet
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#tomography #deeplearning #healthinformatics #patientoutcomes #diagnostics Neda Davoudi

VECTOR’S CHIEF SCIENTIFIC ADVISOR, DR. GEOFFREY HINTON, WINS THE HONDA PRIZE 2019
https://vectorinstitute.ai/2019/09/20/vectors-chief-scientific-advisor-dr-geoffrey-hinton-wins-the-honda-prize-2019/ join : https://t.iss.one/ArtificialIntelligenceArticles