Machine Learning Top 10 Articles for the Past Month (v.July 2019)
https://medium.com/@Mybridge/machine-learning-top-10-articles-for-the-past-month-v-july-2019-178436f99201 https://t.iss.one/ArtificialIntelligenceArticles
https://medium.com/@Mybridge/machine-learning-top-10-articles-for-the-past-month-v-july-2019-178436f99201 https://t.iss.one/ArtificialIntelligenceArticles
Low-Rank Matrix Completion: A Contemporary Survey. arxiv.org/abs/1907.11705
DEAM: Accumulated Momentum with Discriminative Weight for Stochastic Optimization. arxiv.org/abs/1907.11307
Recurrent Aggregation Learning for Multi-View Echocardiographic Sequences Segmentation. arxiv.org/abs/1907.11292
Yann LeCun :
"EGG is a new toolkit that allows researchers and developers to quickly create game simulations in which two neural network agents devise their own discrete communication system in order to solve a task together."
https://code.fb.com/ai-research/egg-toolkit/
https://t.iss.one/ArtificialIntelligenceArticles
"EGG is a new toolkit that allows researchers and developers to quickly create game simulations in which two neural network agents devise their own discrete communication system in order to solve a task together."
https://code.fb.com/ai-research/egg-toolkit/
https://t.iss.one/ArtificialIntelligenceArticles
Facebook Engineering
EGG: A toolkit for language emergence simulations - Facebook Engineering
EGG is a toolkit that allows researchers to create game simulations in which two agents devise their own communication system to solve a task together.
The ACM Turing Lecture on "The #DeepLearning Revolution" is now available
Presented by each winner on the topic of their choice at a forum of their choice in the year they received the ACM A.M. Turing Award https://amturing.acm.org/lectures.cfm
#ArtificialIntelligence #SelfSupervisedLearning
Presented by each winner on the topic of their choice at a forum of their choice in the year they received the ACM A.M. Turing Award https://amturing.acm.org/lectures.cfm
#ArtificialIntelligence #SelfSupervisedLearning
Tensorflow implementation of U-GAT-IT
Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
GitHub, by Junho Kim : https://github.com/taki0112/UGATIT
#tensorflow #unsupervisedlearning #generativemodels
Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
GitHub, by Junho Kim : https://github.com/taki0112/UGATIT
#tensorflow #unsupervisedlearning #generativemodels
GitHub
GitHub - taki0112/UGATIT: Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive…
Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation (ICLR 2020) - taki0112/UGATIT
ConvNet Playground
An interactive visualization tool for exploring Convolutional #NeuralNetworks applied to the task of semantic image search.
Created by Victor Dibia at Fast Forward Labs : https://convnetplayground.fastforwardlabs.com/#/
#datavisualization #deeplearning #machinelearning
An interactive visualization tool for exploring Convolutional #NeuralNetworks applied to the task of semantic image search.
Created by Victor Dibia at Fast Forward Labs : https://convnetplayground.fastforwardlabs.com/#/
#datavisualization #deeplearning #machinelearning
ConvNet Playground
An Interactive Visualization for exploring Convolutional Neural Networks applied to the task of semantic image search. A prototype built by Cloudera Fast Forward Labs.
Implicit Generation and Generalization in Energy-Based Models
Yilun Du and Igor Mordatch : https://arxiv.org/abs/1903.08689
#EnergyBasedModels #MachineLearning #GenerativeModels
Yilun Du and Igor Mordatch : https://arxiv.org/abs/1903.08689
#EnergyBasedModels #MachineLearning #GenerativeModels
arXiv.org
Implicit Generation and Generalization in Energy-Based Models
Energy based models (EBMs) are appealing due to their generality and simplicity in likelihood modeling, but have been traditionally difficult to train. We present techniques to scale MCMC based...
OpenAI’s GPT-2: A Simple Guide to Build the World’s Most Advanced Text Generator in Python
https://www.analyticsvidhya.com/blog/2019/07/openai-gpt2-text-generator-python/
https://www.analyticsvidhya.com/blog/2019/07/openai-gpt2-text-generator-python/
Analytics Vidhya
OpenAI's GPT-2: A Simple Guide to Build the World's Most Advanced Text Generator in Python
OpenAI’s GPT-2 is the world’s most advanced framework for NLP tasks in Python. Build your own GPT-2 AI text generator in Python.
Quantum Computers, Neural Computers, and the future of 0s and 1s.
https://medium.com/@normandipalo/quantum-computers-neural-computers-and-the-future-of-0s-and-1s-ac790ca1f5e4
https://medium.com/@normandipalo/quantum-computers-neural-computers-and-the-future-of-0s-and-1s-ac790ca1f5e4
Medium
Quantum Computers, Neural Computers, and the future of 0s and 1s.
A glimpse into what the future of computing may look like.
FixRes is a simple method for fixing the train-test resolution discrepancy. It can improve the performance of any convolutional neural network architecture.
Github: https://github.com/facebookresearch/FixRes
Article:https://arxiv.org/abs/1906.06423
Github: https://github.com/facebookresearch/FixRes
Article:https://arxiv.org/abs/1906.06423
GitHub
GitHub - facebookresearch/FixRes: This repository reproduces the results of the paper: "Fixing the train-test resolution discrepancy"…
This repository reproduces the results of the paper: "Fixing the train-test resolution discrepancy" https://arxiv.org/abs/1906.06423 - facebookresearch/FixRes
Train and Deploy Machine Learning Model With Web Interface - PyTorch & Flask
Github: https://github.com/imadelh/ML-web-app
Article: https://imadelhanafi.com/posts/train_deploy_ml_model/
Example: https://ml-app.imadelhanafi.com/
Github: https://github.com/imadelh/ML-web-app
Article: https://imadelhanafi.com/posts/train_deploy_ml_model/
Example: https://ml-app.imadelhanafi.com/
GitHub
GitHub - imadelh/ML-web-app: Train and Deploy Simple Machine Learning Model With Web Interface on Jetson Nano
Train and Deploy Simple Machine Learning Model With Web Interface on Jetson Nano - GitHub - imadelh/ML-web-app: Train and Deploy Simple Machine Learning Model With Web Interface on Jetson Nano
Course 4 of the deeplearning.ai TensorFlow Specialization is now available on Coursera! Combine everything you’ve learned to build a sophisticated sunspot prediction model using real-world data. Enroll now: https://www.coursera.org/specializations/tensorflow-in-practice
https://medium.com/syncedreview/baidus-ernie-2-0-beats-bert-and-xlnet-on-nlp-benchmarks-51a8c21aa433
Medium
Baidu’s ERNIE 2.0 Beats BERT and XLNet on NLP Benchmarks
Earlier this year Baidu introduced ERNIE (Enhanced Representation through kNowledge IntEgration), a new knowledge integration language…