Energy-Based Adversarial Training and Video Prediction, NeurIPS 2016
By Yann LeCun, Facebook AI Research
YouTube: https://youtu.be/x4sI5qO6O2Y
#DeepLearning #EnergyBasedModels #UnsupervisedLearning
By Yann LeCun, Facebook AI Research
YouTube: https://youtu.be/x4sI5qO6O2Y
#DeepLearning #EnergyBasedModels #UnsupervisedLearning
YouTube
Energy-Based Adversarial Training and Video Prediction, NIPS 2016 | Yann LeCun, Facebook AI Research
NIPS 2016 Workshop on Adversarial Training https://arxiv.org/abs/1609.03126 We introduce the "Energy-based Generative Adversarial Network" model (EBGAN) whic...
Deep TabNine: The all-language autocompleter.
It uses machine learning to provide responsive, reliable, and relevant suggestions.
Traditional autocompleters suggest one word at a time while Deep TabNine, based on GPT-2 and trained on 22 million Github files suggest way much more.
Isn't it cool ! Give it a try 🙌
Website: https://tabnine.com/
Github: https://github.com/zxqfl/tabnine
It uses machine learning to provide responsive, reliable, and relevant suggestions.
Traditional autocompleters suggest one word at a time while Deep TabNine, based on GPT-2 and trained on 22 million Github files suggest way much more.
Isn't it cool ! Give it a try 🙌
Website: https://tabnine.com/
Github: https://github.com/zxqfl/tabnine
Tabnine
Tabnine AI Code Assistant | Smarter AI Coding Agents. Total Enterprise Control.
Tabnine is the AI code assistant that accelerates and simplifies software development while keeping your code private, secure, and compliant.
"Advanced NLP with spaCy"
By Ines Montani : https://course.spacy.io
#machinelearning #nlp #naturallanguageprocessing
By Ines Montani : https://course.spacy.io
#machinelearning #nlp #naturallanguageprocessing
"Rapid research framework for PyTorch. The researcher's version of Keras"
GitHub, by William Falcon : https://github.com/williamFalcon/pytorch-lightning
#deeplearning #pytorch #research
GitHub, by William Falcon : https://github.com/williamFalcon/pytorch-lightning
#deeplearning #pytorch #research
GitHub
GitHub - Lightning-AI/pytorch-lightning: Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes. - Lightning-AI/pytorch-lightning
Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview
Jiawei Zhang : https://arxiv.org/abs/1908.00187
#MachineLearning #NeuralEvolutionary #MachineLearning
Jiawei Zhang : https://arxiv.org/abs/1908.00187
#MachineLearning #NeuralEvolutionary #MachineLearning
Functional Regularisation for Continual Learning
Titsias et al.: https://arxiv.org/abs/1901.11356
#ArtificialIntelligence #BayesianInference #MachineLearning
Titsias et al.: https://arxiv.org/abs/1901.11356
#ArtificialIntelligence #BayesianInference #MachineLearning
arXiv.org
Functional Regularisation for Continual Learning with Gaussian Processes
We introduce a framework for Continual Learning (CL) based on Bayesian inference over the function space rather than the parameters of a deep neural network. This method, referred to as functional...
Disentangling Disentanglement in Variational Autoencoders
Mathieu et al.: https://proceedings.mlr.press/v97/mathieu19a.html
#DeepLearning #VariationalAutoencoders #VAE
Mathieu et al.: https://proceedings.mlr.press/v97/mathieu19a.html
#DeepLearning #VariationalAutoencoders #VAE
PMLR
Disentangling Disentanglement in Variational Autoencoders
We develop a generalisation of disentanglement in variational autoencoders (VAEs)—decomposition of the latent representation—characterising it as the fulfilm...
MelNet: A Generative Model for Audio in the Frequency Domain
Sean Vasquez, Mike Lewis: https://arxiv.org/abs/1906.01083
Blog: https://sjvasquez.github.io/blog/melnet/
#ArtificialIntelligence #AudioProcessing #MachineLearning
Sean Vasquez, Mike Lewis: https://arxiv.org/abs/1906.01083
Blog: https://sjvasquez.github.io/blog/melnet/
#ArtificialIntelligence #AudioProcessing #MachineLearning
Welcome this Chinese DeepLearning Chip called “Tianjic”.
Paper: https://www.nature.com/articles/s41586-019-1424-8
It can run traditional deep learning code and also perform "neuromorophic" operations in the same circuitry.
Paper: https://www.nature.com/articles/s41586-019-1424-8
It can run traditional deep learning code and also perform "neuromorophic" operations in the same circuitry.
"Deep Boltzmann Machines"
Ruslan Salakhutdinov and Geoffrey Hinton : https://proceedings.mlr.press/v5/salakhutdinov09a/salakhutdinov09a.pdf
#BoltzmannMachines #DeepBoltzmannMachines #DeepLearning
Ruslan Salakhutdinov and Geoffrey Hinton : https://proceedings.mlr.press/v5/salakhutdinov09a/salakhutdinov09a.pdf
#BoltzmannMachines #DeepBoltzmannMachines #DeepLearning
CS231N: Convolutional Neural Networks for Visual Recognition
Stanford University School of Engineering : https://www.youtube.com/playlist?list=PLzUTmXVwsnXod6WNdg57Yc3zFx_f-RYsq
#ArtificialIntelligence #MachineLearning #NeuralNetworks
Stanford University School of Engineering : https://www.youtube.com/playlist?list=PLzUTmXVwsnXod6WNdg57Yc3zFx_f-RYsq
#ArtificialIntelligence #MachineLearning #NeuralNetworks
YouTube
CS231N 2017
Share your videos with friends, family, and the world
CS224N Natural Language Processing with Deep Learning
Stanford University School of Engineering
:
https://www.youtube.com/playlist?list=PLU40WL8Ol94IJzQtileLTqGZuXtGlLMP_
#NaturalLanguageProcessing #MachineLearning #DeepLearning
Stanford University School of Engineering
:
https://www.youtube.com/playlist?list=PLU40WL8Ol94IJzQtileLTqGZuXtGlLMP_
#NaturalLanguageProcessing #MachineLearning #DeepLearning
Build a self-driving for about $300 using a RasberryPi. 😊
https://towardsdatascience.com/deeppicar-part-1-102e03c83f2c
https://towardsdatascience.com/deeppicar-part-1-102e03c83f2c
Medium
DeepPiCar — Part 1: How to Build a Deep Learning, Self Driving Robotic Car on a Shoestring Budget
An overview of how to build a Raspberry Pi and TensorFlow powered self driving robotic car
Introduction to Reinforcement Learning
By DeepMind. YouTube: https://www.youtube.com/watch?list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ&time_continue=5&v=2pWv7GOvuf0
#deeplearning #artificialintelligence #reinforcementlearning
By DeepMind. YouTube: https://www.youtube.com/watch?list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ&time_continue=5&v=2pWv7GOvuf0
#deeplearning #artificialintelligence #reinforcementlearning
YouTube
RL Course by David Silver - Lecture 1: Introduction to Reinforcement Learning
#Reinforcement Learning Course by David Silver# Lecture 1: Introduction to Reinforcement Learning
#Slides and more info about the course: https://goo.gl/vUiyjq
#Slides and more info about the course: https://goo.gl/vUiyjq
Tutorial on Graph Neural Networks for Computer Vision and Beyond (Part 1)
https://medium.com/@BorisAKnyazev/tutorial-on-graph-neural-networks-for-computer-vision-and-beyond-part-1-3d9fada3b80d
https://medium.com/@BorisAKnyazev/tutorial-on-graph-neural-networks-for-computer-vision-and-beyond-part-1-3d9fada3b80d
Medium
Tutorial on Graph Neural Networks for Computer Vision and Beyond (Part 1)
I’m answering questions that AI/ML/CV people not familiar with graphs or graph neural networks typically ask. I provide PyTorch examples …
NeurIPS 2019 : Disentanglement Challenge
Blog by Max Planck Institute for Intelligent Systems: https://www.aicrowd.com/challenges/neurips-2019-disentanglement-challenge
#DeepLearning #Disentanglement #NeurIPS #NeurIPS2019
Blog by Max Planck Institute for Intelligent Systems: https://www.aicrowd.com/challenges/neurips-2019-disentanglement-challenge
#DeepLearning #Disentanglement #NeurIPS #NeurIPS2019
AIcrowd | NeurIPS 2019 : Disentanglement Challenge | Challenges
Disentanglement: from simulation to real-world
New Frontiers of Automated Mechanism Design for Pricing and Auctions by Maria-Florina Balcan, @mldcmu, Tuomas Sandholm, Ellen Vitercik @csdatcmu
Learn more → https://mld.ai/y1m
Tutorial Video Part I: https://youtu.be/buK3KXZcGAI
Tutorial Video Part II: https://youtu.be/T8gaK4Yw4zI
#MechanismDesign #GameTheory #Tutorial #MachineLearning #Optimization #ML
Learn more → https://mld.ai/y1m
Tutorial Video Part I: https://youtu.be/buK3KXZcGAI
Tutorial Video Part II: https://youtu.be/T8gaK4Yw4zI
#MechanismDesign #GameTheory #Tutorial #MachineLearning #Optimization #ML
Google
EC19 New Frontiers of Automated Mechanism Design for Pricing and Auctions