Head animation from single shot by #SamsungAI team
Samsung researchers have released a model that can generate faces in new poses from just a single image/frame (for each of face, pose). Done by building a well-trained landmark model in advance & one-shotting from that, using keypoints, adaptive instance norms and GANs. Model performs no 3D face modelling!
ArXiV: https://arxiv.org/abs/1905.08233v1
Youtube: https://www.youtube.com/watch?v=p1b5aiTrGzY
#GAN #CV #DL
Samsung researchers have released a model that can generate faces in new poses from just a single image/frame (for each of face, pose). Done by building a well-trained landmark model in advance & one-shotting from that, using keypoints, adaptive instance norms and GANs. Model performs no 3D face modelling!
ArXiV: https://arxiv.org/abs/1905.08233v1
Youtube: https://www.youtube.com/watch?v=p1b5aiTrGzY
#GAN #CV #DL
arXiv.org
Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
Several recent works have shown how highly realistic human head images can be obtained by training convolutional neural networks to generate them. In order to create a personalized talking head...
21 Must-Know Open Source Tools for Machine Learning you Probably Aren’t Using (but should!)
https://www.analyticsvidhya.com/blog/2019/07/21-open-source-machine-learning-tools/
https://www.analyticsvidhya.com/blog/2019/07/21-open-source-machine-learning-tools/
Analytics Vidhya
21 Must-Know Open Source Tools for Machine Learning you Probably Aren't Using (but should!)
Machine learning tools for data scientists. Here are the 21 open source machine learning tools for five machine learning aspects.
Five fundamental truths about algorithms for anyone living in the Digital Age. I would love to hear your thoughts! #machinelearning #bigdata #algorithms #artificialintelligence
https://www.youtube.com/watch?v=XYCq3K_XxZY&feature=share&fbclid=IwAR2CCOiLZgbNXG0AQC5hRfTNhETBlJ60ieQmVgXSYlXrwRHhugk_f01NSvg
https://www.youtube.com/watch?v=XYCq3K_XxZY&feature=share&fbclid=IwAR2CCOiLZgbNXG0AQC5hRfTNhETBlJ60ieQmVgXSYlXrwRHhugk_f01NSvg
YouTube
The power and perils of algorithms | Gah-Yi Ban | TEDxLondonBusinessSchool
Gah-Yi Ban's talk hopes to help us understand the role of algorithms in our present lives, and how we can shape their role in our future. Gah-Yi Ban is a pro...
Applied Machine Learning Engineer at Amazon
EAST PALO ALTO, CA, USA
https://www.marktechpost.com/job/applied-machine-learning-engineer-at-amazon/
https://t.iss.one/ArtificialIntelligenceArticles
EAST PALO ALTO, CA, USA
https://www.marktechpost.com/job/applied-machine-learning-engineer-at-amazon/
https://t.iss.one/ArtificialIntelligenceArticles
MarkTechPost
Applied Machine Learning Engineer at Amazon | MarkTechPost
Description Amazon Personalize is a machine learning service that makes it easy for developers to create individualized recommendations for customers using their applications. We’re a fast-growing business within AWS AI, where you’ll have a unique opportunity…
Ten Lectures and Forty-Two Open Problems in the Mathematics of Data Science: MIT
Download Link: https://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-of-data-science-fall-2015/lecture-notes/MIT18_S096F15_TenLec.pdf
Download Link: https://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-of-data-science-fall-2015/lecture-notes/MIT18_S096F15_TenLec.pdf
MIT OpenCourseWare
Lecture Notes | Topics in Mathematics of Data Science | Mathematics | MIT OpenCourseWare
This section provides the schedule of course topics and the lecture notes used for the course.
From Planck Area to Graph Theory: Topologically Distinct Black Hole Microstates. arxiv.org/abs/1907.03090
M3D-GAN: Multi-Modal Multi-Domain Translation with Universal Attention
Ma et al.: https://arxiv.org/abs/1907.04378
#MachineLearning #DeepLearning #ArtificialIntelligence
Ma et al.: https://arxiv.org/abs/1907.04378
#MachineLearning #DeepLearning #ArtificialIntelligence
arXiv.org
M3D-GAN: Multi-Modal Multi-Domain Translation with Universal Attention
Generative adversarial networks have led to significant advances in
cross-modal/domain translation. However, typically these networks are designed
for a specific task (e.g., dialogue generation or...
cross-modal/domain translation. However, typically these networks are designed
for a specific task (e.g., dialogue generation or...
Sparse Networks from Scratch: Faster Training without Losing Performance
Tim Dettmers and Luke Zettlemoyer: https://arxiv.org/abs/1907.04840
Paper: https://arxiv.org/abs/1907.04840
Blog post: https://timdettmers.com/2019/07/11/sparse-networks-from-scratch/
Code: https://github.com/TimDettmers/sparse_learning
#MachineLearning #NeuralComputing #EvolutionaryComputing
Tim Dettmers and Luke Zettlemoyer: https://arxiv.org/abs/1907.04840
Paper: https://arxiv.org/abs/1907.04840
Blog post: https://timdettmers.com/2019/07/11/sparse-networks-from-scratch/
Code: https://github.com/TimDettmers/sparse_learning
#MachineLearning #NeuralComputing #EvolutionaryComputing
arXiv.org
Sparse Networks from Scratch: Faster Training without Losing Performance
We demonstrate the possibility of what we call sparse learning: accelerated training of deep neural networks that maintain sparse weights throughout training while achieving dense performance...
Interesting robotics application from CVPR 2019! paper: https://www.profillic.com/paper/arxiv:1901.04780
code:https://www.profillic.com/paper/arxiv:1901.04780/code
Densefusion: The model takes an RGB-D image as input and predicts the 6D pose of the each object in the frame.
code:https://www.profillic.com/paper/arxiv:1901.04780/code
Densefusion: The model takes an RGB-D image as input and predicts the 6D pose of the each object in the frame.
Profillic
Profillic: AI research & source code to supercharge your projects
Explore state-of-the-art in machine learning, AI, and robotics research. Browse papers, source code, models, and more by topics and authors. Connect with researchers and engineers working on related problems in machine learning, deep learning, natural language…
Machine Learning for Everyone.
The best general intro post about Machine Learning, covering everything you need to know not to get overxcited about SkyNet and to get general understanding of all #ML / #AI hype. You can surely save this post into «Saved messages» and forward it to your friends to make them familiar with the subject
Link: https://vas3k.com/blog/machine_learning/
#entrylevel #novice #general
The best general intro post about Machine Learning, covering everything you need to know not to get overxcited about SkyNet and to get general understanding of all #ML / #AI hype. You can surely save this post into «Saved messages» and forward it to your friends to make them familiar with the subject
Link: https://vas3k.com/blog/machine_learning/
#entrylevel #novice #general
Vas3K
None
New deep learning framework from Facebook
Pythia is a deep learning framework that supports multitasking in the vision and language domain. Built on our open-source #PyTorch framework, the modular, plug-and-play design enables researchers to quickly build, reproduce, and benchmark AI models. #Pythia is designed for vision and language tasks, such as answering questions related to visual data and automatically generating image captions.
Link: https://code.fb.com/ai-research/pythia/
GitHub: https://github.com/facebookresearch/pythia
#Facebook #FacebookAI #DL #CV #multimodal
Pythia is a deep learning framework that supports multitasking in the vision and language domain. Built on our open-source #PyTorch framework, the modular, plug-and-play design enables researchers to quickly build, reproduce, and benchmark AI models. #Pythia is designed for vision and language tasks, such as answering questions related to visual data and automatically generating image captions.
Link: https://code.fb.com/ai-research/pythia/
GitHub: https://github.com/facebookresearch/pythia
#Facebook #FacebookAI #DL #CV #multimodal
Engineering at Meta
Releasing Pythia for vision and language multimodal AI models
Pythia is a new open source deep learning framework that enables researchers to quickly build, reproduce, and benchmark AI models.
A Recipe for Training Neural Networks by Andrej Karpathy
New article written by Andrej Karpathy distilling a bunch of useful heuristics for training neural nets. The post is full of real-world knowledge and how-to details that are not taught in books and often take endless hours to learn the hard way.
Link: https://karpathy.github.io/2019/04/25/recipe/
#tipsandtricks #karpathy #tutorial #nn #ml #dl
New article written by Andrej Karpathy distilling a bunch of useful heuristics for training neural nets. The post is full of real-world knowledge and how-to details that are not taught in books and often take endless hours to learn the hard way.
Link: https://karpathy.github.io/2019/04/25/recipe/
#tipsandtricks #karpathy #tutorial #nn #ml #dl
karpathy.github.io
A Recipe for Training Neural Networks
Musings of a Computer Scientist.
Awesome new paper from FAIR:
1. A new type of large-scale memory layer that uses product keys (FAISS-like indexing with product quantization)
2. Replace some layers in a BERT-like architecture by these Product Key Memory layers.
.....
3. PROFIT: better perplexity than BERT for half the computation.
NLP tasks require lots of memory. This is a good way to give loads of memory to a neural net while making it computationally practical by making it sparsely activated. PKM layers can be seen as having a sort of "winners take all" competition to sparsify the activities.
https://arxiv.org/abs/1907.05242
1. A new type of large-scale memory layer that uses product keys (FAISS-like indexing with product quantization)
2. Replace some layers in a BERT-like architecture by these Product Key Memory layers.
.....
3. PROFIT: better perplexity than BERT for half the computation.
NLP tasks require lots of memory. This is a good way to give loads of memory to a neural net while making it computationally practical by making it sparsely activated. PKM layers can be seen as having a sort of "winners take all" competition to sparsify the activities.
https://arxiv.org/abs/1907.05242
arXiv.org
Large Memory Layers with Product Keys
This paper introduces a structured memory which can be easily integrated into a neural network. The memory is very large by design and significantly increases the capacity of the architecture, by...
Check-out book:
Generative Adversarial Networks with Python https://machinelearningmastery.com/generative_adversarial_networks/
Generative Adversarial Networks with Python https://machinelearningmastery.com/generative_adversarial_networks/
AI predictions for 2019 from Rumman Chowdury, Hilary Mason, Andrew Ng and yours truly https://venturebeat.com/2019/01/02/ai-predictions-for-2019-from-yann-lecun-hilary-mason-andrew-ng-and-rumman-chowdhury/
VentureBeat
AI predictions for 2019 from Yann LeCun, Hilary Mason, Andrew Ng, and Rumman Chowdhury
VentureBeat spoke with Google Brain cofounder Andrew Ng, Fast Forward Labs founder Hilary Mason, Facebook AI Research founder Yann LeCun, and Accenture responsible AI global lead Dr. Rumman Chowdhury about key milestones of 2018 and what lies ahead for 2019.
10 of the Best Tensorflow Courses to Learn Machine Learning from Coursera and Udemy
https://dev.to/javinpaul/10-of-the-best-tensorflow-courses-to-learn-machine-learning-from-coursera-and-udemy-37bf
https://dev.to/javinpaul/10-of-the-best-tensorflow-courses-to-learn-machine-learning-from-coursera-and-udemy-37bf
DEV Community
10 Best Tensorflow Online Courses from Coursera and Udemy for Beginners
Learn Machine learning with Tensorflow from the best online courses and certifications from Coursera, Udemy, and Pluralsight.