2020 is off to a good start! Yoshua Bengio named La Presse's Science Personality of the Year. https://plus.lapresse.ca/screens/d61f0911-4ae4-44cc-8b8c-f849f103cac4__7C___0.html
Postdoctoral and Research Fellow positions in Artificial Intelligence -- FCAI https://fcai.fi/postdocs
"Deep learning, science, engineering, research, and terminology"
A Dialogue between Yoshua Bengio and Gary Marcus : https://medium.com/@GaryMarcus/deep-learning-science-engineering-research-and-terminology-292a747a94d3
#AIDebate
A Dialogue between Yoshua Bengio and Gary Marcus : https://medium.com/@GaryMarcus/deep-learning-science-engineering-research-and-terminology-292a747a94d3
#AIDebate
Medium
Deep learning, science, engineering, research, and terminology
A Dialogue between Yoshua Bengio and Gary Marcus
WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia
Paper: https://openreview.net/pdf?id=rkeYL1SFvH
Github: https://github.com/facebookresearch/LASER
Paper: https://openreview.net/pdf?id=rkeYL1SFvH
Github: https://github.com/facebookresearch/LASER
Deep Learning Models
A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks.
By Sebastian Raschka : https://github.com/rasbt/deeplearning-models
#ArtificialIntelligence #DeepLearning #MachineLearning
A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks.
By Sebastian Raschka : https://github.com/rasbt/deeplearning-models
#ArtificialIntelligence #DeepLearning #MachineLearning
GitHub
GitHub - rasbt/deeplearning-models: A collection of various deep learning architectures, models, and tips
A collection of various deep learning architectures, models, and tips - rasbt/deeplearning-models
Chip-to-chip quantum teleportation and multi-photon entanglement in silicon
https://www.nature.com/articles/s41567-019-0727-x
https://www.nature.com/articles/s41567-019-0727-x
Nature
Chip-to-chip quantum teleportation and multi-photon entanglement in silicon
Nature Physics - Four single-photon states are generated and entangled on a single micrometre-scale silicon chip, and provide the basis for the demonstration of chip-to-chip quantum teleportation.
[https://www.lapresse.ca/actualites/sciences/201912/31/01-5255427-personnalite-de-lanneesciences-yoshua-bengio.php](https://www.lapresse.ca/actualites/sciences/201912/31/01-5255427-personnalite-de-lanneesciences-yoshua-bengio.php)
La Presse
Personnalité de l’année/Sciences : Yoshua Bengio
Il n’y a pas de prix Nobel en informatique. Mais il y a un prix Turing, nommé en l’honneur d’Alan Turing, mathématicien britannique dont les travaux ont ou...
Machine Learning 2020 - The Year of MI
Part 1 - Machine Learning For Beginners - Basics
https://youtu.be/E3l_aeGjkeI
Part 2 - MI environment
https://youtu.be/HqyrqxyDwPU
Part 3 - Python Decision Tree (Theory)
https://youtu.be/8isUCINSmys
Part 4 - Python Decision Tree (Coding)
https://youtu.be/24mxQzd3EsU
Part 5 - Python Decision Tree (Graphiviz)
https://youtu.be/aVEfKRfWjHc
Part 6 - Knn(Friend Recommender)
https://youtu.be/LK0zgA6Mr6k
Part 7- 5-Fold Cross Validation
https://youtu.be/Zx5cz8pXnOM
Part 1 - Machine Learning For Beginners - Basics
https://youtu.be/E3l_aeGjkeI
Part 2 - MI environment
https://youtu.be/HqyrqxyDwPU
Part 3 - Python Decision Tree (Theory)
https://youtu.be/8isUCINSmys
Part 4 - Python Decision Tree (Coding)
https://youtu.be/24mxQzd3EsU
Part 5 - Python Decision Tree (Graphiviz)
https://youtu.be/aVEfKRfWjHc
Part 6 - Knn(Friend Recommender)
https://youtu.be/LK0zgA6Mr6k
Part 7- 5-Fold Cross Validation
https://youtu.be/Zx5cz8pXnOM
YouTube
Machine Learning Tutorial Part 1 | Machine Learning For Beginners
This Machine Learning tutorial will introduce you to the different areas of Machine Learning and Artificial Intelligence. In this part of the course you will learn about the three different learning types (Unsupervised learning, Supervised Learning and Reinforcement…
Could Lab-Grown Brains Develop Consciousness?
https://singularityhub.com/2019/07/03/could-lab-grown-brains-develop-consciousness/
https://singularityhub.com/2019/07/03/could-lab-grown-brains-develop-consciousness/
Singularity Hub
Could Lab-Grown Brains Develop Consciousness?
A week after transplant, the dissected neural clusters spontaneously formed multiple networks, and the team found synchronized waves throughout the network.
How to generate ideas in Machine Learning?
Asadulaev Arip : https://medium.com/datadriveninvestor/how-to-generate-ideas-in-machine-learning-bdb9a7267392
#ArtificialIntelligence #MachineLearning #NeuralNetworks
Asadulaev Arip : https://medium.com/datadriveninvestor/how-to-generate-ideas-in-machine-learning-bdb9a7267392
#ArtificialIntelligence #MachineLearning #NeuralNetworks
Medium
How to generate ideas in Machine Learning?
Little story about https://www.infornopolitan.xyz
Connections between Support Vector Machines, Wasserstein distance and gradient-penalty GANs
Alexia Jolicoeur-Martineau, Ioannis Mitliagkas : https://arxiv.org/abs/1910.06922
#GenerativeAdversarialNetworks #MachineLearning #SupportVectorMachines
Alexia Jolicoeur-Martineau, Ioannis Mitliagkas : https://arxiv.org/abs/1910.06922
#GenerativeAdversarialNetworks #MachineLearning #SupportVectorMachines
arXiv.org
Gradient penalty from a maximum margin perspective
A popular heuristic for improved performance in Generative adversarial networks (GANs) is to use some form of gradient penalty on the discriminator. This gradient penalty was originally motivated...
Debate of the year in ai quotes lamb's work
The Neural-symbolic cognitive reasoning reasoning was mentioned last week in what was considered the great debate about the future of ai in the world: https://www.jornaldocomercio.com/_conteudo/colunas/mercado_digital/2019/12/718693-debate-do-ano-em-ia-cita-trabalho-de-lamb.html
The Neural-symbolic cognitive reasoning reasoning was mentioned last week in what was considered the great debate about the future of ai in the world: https://www.jornaldocomercio.com/_conteudo/colunas/mercado_digital/2019/12/718693-debate-do-ano-em-ia-cita-trabalho-de-lamb.html
Jornal do Comércio
Debate do ano em IA cita trabalho de Lamb
Gary Marcus, professor emérito da New York University (NYU), destacou o trabalho como sendo uma referência por apresentar uma perspectiva futura da IA
SpeechBrain
A PyTorch-based Speech Toolkit
Video, by Mirco Ravanelli : https://youtube.com/watch?v=XETiKbN9ojE
: https://speechbrain.github.io
#speechbrain #NLP #DeepLearning
https://t.iss.one/ArtificialIntelligenceArticles
A PyTorch-based Speech Toolkit
Video, by Mirco Ravanelli : https://youtube.com/watch?v=XETiKbN9ojE
: https://speechbrain.github.io
#speechbrain #NLP #DeepLearning
https://t.iss.one/ArtificialIntelligenceArticles
YouTube
The SpeechBrain Project
SpeechBrain is an open-source and all-in-one speech toolkit relying on PyTorch.
The goal is to create a single, flexible, and user-friendly toolkit that can be used to easily develop state-of-the-art speech technologies
The goal is to create a single, flexible, and user-friendly toolkit that can be used to easily develop state-of-the-art speech technologies
Nice work.
But there is an earlier large-scale study by an NYU team using a ConvNet-powered mammogram analyzer.
And, unlike the DeepMind system, it's open source!
Paper: https://ieeexplore.ieee.org/document/8861376
GitHub: https://github.com/nyukat/breast_cancer_classifier
But there is an earlier large-scale study by an NYU team using a ConvNet-powered mammogram analyzer.
And, unlike the DeepMind system, it's open source!
Paper: https://ieeexplore.ieee.org/document/8861376
GitHub: https://github.com/nyukat/breast_cancer_classifier
Language Models as Knowledge Bases?
Petroni et al.: https://arxiv.org/abs/1909.01066
#Transformers #NaturalLanguageProcessing #MachineLearning
Petroni et al.: https://arxiv.org/abs/1909.01066
#Transformers #NaturalLanguageProcessing #MachineLearning
arXiv.org
Language Models as Knowledge Bases?
Recent progress in pretraining language models on large textual corpora led to a surge of improvements for downstream NLP tasks. Whilst learning linguistic knowledge, these models may also be...
Restoring ancient text using deep learning: a case study on Greek epigraphy"
Assael et al.: https://arxiv.org/abs/1910.06262
Code: https://github.com/sommerschield/ancient-text-restoration
#ArtificialIntelligence #DeepLearning #NeuralNetworks
Assael et al.: https://arxiv.org/abs/1910.06262
Code: https://github.com/sommerschield/ancient-text-restoration
#ArtificialIntelligence #DeepLearning #NeuralNetworks
arXiv.org
Restoring ancient text using deep learning: a case study on Greek epigraphy
Ancient history relies on disciplines such as epigraphy, the study of ancient inscribed texts, for evidence of the recorded past. However, these texts, "inscriptions", are often damaged over the...
Deep learning model for breast cancer detection beats five full-time radiologists and previous SOTA models from NYU and MIT
Paper: https://arxiv.org/pdf/1912.11027.pdf
Paper: https://arxiv.org/pdf/1912.11027.pdf
International evaluation of an AI system for breast cancer screening
https://www.nature.com/articles/s41586-019-1799-6
https://www.nature.com/articles/s41586-019-1799-6
Nature
International evaluation of an AI system for breast cancer screening
Nature - An artificial intelligence (AI) system performs as well as or better than radiologists at detecting breast cancer from mammograms, and using a combination of AI and human inputs could help...
ArtificialIntelligenceArticles
International evaluation of an AI system for breast cancer screening https://www.nature.com/articles/s41586-019-1799-6
Chest Radiograph Interpretation with deep learning ✔️
https://pubs.rsna.org/doi/10.1148/radiol.2019191293
Evaluation of an AI system for breast cancer screening ✔️
https://nature.com/articles/s41586-019-1799-6
impressive work https://health.google
https://pubs.rsna.org/doi/10.1148/radiol.2019191293
Evaluation of an AI system for breast cancer screening ✔️
https://nature.com/articles/s41586-019-1799-6
impressive work https://health.google
Radiology
Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population…
Background Deep learning has the potential to augment the use of chest radiography in clinical radiology, but challenges include poor generalizability, spectrum bias, and difficulty comparing across studies. Purpose To develop and evaluate deep learning models…