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…
Learning Symbolic Physics with Graph Networks
Miles D. Cranmer, Rui Xu, Peter Battaglia, Shirley Ho : https://arxiv.org/abs/1909.05862 #GraphNetworks
#MachineLearning #Physics
Miles D. Cranmer, Rui Xu, Peter Battaglia, Shirley Ho : https://arxiv.org/abs/1909.05862 #GraphNetworks
#MachineLearning #Physics
The UNC School of Medicine lab of Zoe McElligott, PhD, found that alcohol consumption is regulated by the activity of a particular set of neurons in a specific brain region, a discovery that could lead to a better understanding of why some casual drinkers. https://www.eurekalert.org/pub_releases/2019-12/uonc-sdk121219.php
EurekAlert!
Scientists discover key neural circuit regulating alcohol consumption
Published in the Journal of Neuroscience, UNC-Chapel Hill research pinpoints a specific neural circuit that when altered caused animal models to drink less alcohol.
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Tanaka et al.: https://papers.nips.cc/paper/9060-from-deep-learning-to-mechanistic-understanding-in-neuroscience-the-structure-of-retinal-prediction
#DeepLearning #Neuroscience #NeurIPS2019
Tanaka et al.: https://papers.nips.cc/paper/9060-from-deep-learning-to-mechanistic-understanding-in-neuroscience-the-structure-of-retinal-prediction
#DeepLearning #Neuroscience #NeurIPS2019
papers.nips.cc
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Electronic Proceedings of Neural Information Processing Systems
The Decade of Deep Learning
https://leogao.dev/2019/12/31/The-Decade-of-Deep-Learning/
https://leogao.dev/2019/12/31/The-Decade-of-Deep-Learning/
Leo Gao
The Decade of Deep Learning
As the 2010’s draw to a close, it’s worth taking a look back at the monumental progress that has been made in Deep Learning in this decade.[1] Driven by the development of ever-more powerful comput
Selective Brain Damage: Measuring the Disparate Impact of Model Compression
Sara Hooker, Aaron Courville, Yann Dauphin, Andrea Frome
https://weightpruningdamage.github.io/
SLIDES
https://drive.google.com/file/d/1VIeV7l9x-KXdT_UdZB54GQxhGHRRQ79T/view
Sara Hooker, Aaron Courville, Yann Dauphin, Andrea Frome
https://weightpruningdamage.github.io/
SLIDES
https://drive.google.com/file/d/1VIeV7l9x-KXdT_UdZB54GQxhGHRRQ79T/view
Deep Neural Network Pruning
Selective Brain Damage
What do pruned deep neural networks forget?
2019’s Top Open Source Machine Learning Projects
https://heartbeat.fritz.ai/2019s-top-open-source-machine-learning-projects-3cd082a02f78
https://heartbeat.fritz.ai/2019s-top-open-source-machine-learning-projects-3cd082a02f78
Fritz ai
2019’s Top Open Source Machine Learning Projects - Fritz ai
In this piece, we’ll look at some of the top open source machine learning projects in 2019, as ranked by MyBridge. Real-Time-Voice-Cloning (13.7K ⭐️) This project is an implementation of the SV2TTS paper with a vocoder that works in real-time.… Continue reading…
keras-ocr
A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model
GitHub, by Fausto Morales : https://github.com/faustomorales/keras-ocr
#ArtificialIntelligence #DeepLearning #MachineLearning
A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model
GitHub, by Fausto Morales : https://github.com/faustomorales/keras-ocr
#ArtificialIntelligence #DeepLearning #MachineLearning
GitHub
GitHub - faustomorales/keras-ocr: A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model.
A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model. - faustomorales/keras-ocr
Deep Learning for 3D Point Clouds: A Survey
Guo et al.: https://arxiv.org/abs/1912.12033
#DeepLearning #MachineLearning #Robotics
Guo et al.: https://arxiv.org/abs/1912.12033
#DeepLearning #MachineLearning #Robotics
What can the brain teach us about building artificial intelligence?
Dileep George : https://arxiv.org/abs/1909.01561
#ArtificialIntelligence #Neurons #Brain
Dileep George : https://arxiv.org/abs/1909.01561
#ArtificialIntelligence #Neurons #Brain
exBERT- A Visual Analysis Tool to Explore Learned Representations in Transformers Models
Benjamin Hoover, Hendrik Strobelt, Sebastian Gehrmann : https://exbert.net
#NLP #BERT #LanguageModel
Benjamin Hoover, Hendrik Strobelt, Sebastian Gehrmann : https://exbert.net
#NLP #BERT #LanguageModel