Forecaster: A Graph Transformer for Forecasting Spatial and Time-Dependent Data
Yang Li, José M. F. Moura : https://arxiv.org/abs/1909.04019v3
#MachineLearning #ArtificialIntelligence #Transformer
Yang Li, José M. F. Moura : https://arxiv.org/abs/1909.04019v3
#MachineLearning #ArtificialIntelligence #Transformer
Help detect serious head injuries by participating in our latest competition, Intracranial Hemorrhage Detection by @RSNA | Read more and Join today!
https://www.kaggle.com/c/rsna-intracranial-hemorrhage-detection
https://www.kaggle.com/c/rsna-intracranial-hemorrhage-detection
Kaggle
RSNA Intracranial Hemorrhage Detection
Identify acute intracranial hemorrhage and its subtypes
Robotics surgeries may currently be an expensive proposition for hospitals, but robots and artificial intelligence will certainly play a major role in the healthcare sector in the future.
Several startups such as DiFacto Robotics, SigTuple and Aindra are working to bring new technologies to reality in India. A group of top executives from hospital chains, investment firms and startups discussed the future of healthcare at the News Corp VCCircle Healthcare Investment Summit, held in Mumbai recently.
https://www.youtube.com/watch?v=1arrmk4XWZE
Several startups such as DiFacto Robotics, SigTuple and Aindra are working to bring new technologies to reality in India. A group of top executives from hospital chains, investment firms and startups discussed the future of healthcare at the News Corp VCCircle Healthcare Investment Summit, held in Mumbai recently.
https://www.youtube.com/watch?v=1arrmk4XWZE
YouTube
How robotics, artificial intelligence can change healthcare sector
Robotics surgeries may currently be an expensive proposition for hospitals, but robots and artificial intelligence will certainly play a major role in the healthcare sector in the future. Several startups such as DiFacto Robotics, SigTuple and Aindra are…
Full Time Opportunities for PhD Students - AI Development Program
#Microsoft
#Redmond, Washington, United States
https://careers.microsoft.com/us/en/job/660559/Full-Time-Opportunities-for-PhD-Students-AI-Development-Program
#Microsoft
#Redmond, Washington, United States
https://careers.microsoft.com/us/en/job/660559/Full-Time-Opportunities-for-PhD-Students-AI-Development-Program
Project Ihmehimmeli: Temporal Coding in Spiking Neural Networks
Blog by Iulia-Maria Comșa and Krzysztof Potempa : https://ai.googleblog.com/2019/09/project-ihmehimmeli-temporal-coding-in.html
#neuralnetworks #machinelearning #artificialintelligence
Blog by Iulia-Maria Comșa and Krzysztof Potempa : https://ai.googleblog.com/2019/09/project-ihmehimmeli-temporal-coding-in.html
#neuralnetworks #machinelearning #artificialintelligence
Googleblog
Project Ihmehimmeli: Temporal Coding in Spiking Neural Networks
Neural-Network Pioneer Yann LeCun on AI and Physics
https://harvardmagazine.com/2019/09/neural-network-pioneer-yann-lecun-on-ai-and-physics#disqus_thread
https://t.iss.one/ArtificialIntelligenceArticles
https://harvardmagazine.com/2019/09/neural-network-pioneer-yann-lecun-on-ai-and-physics#disqus_thread
https://t.iss.one/ArtificialIntelligenceArticles
Harvard Magazine
Neural-Network Pioneer Yann LeCun on AI and Physics
The physics department confers its Loeb lectureship on an influential non-physicist.
Explore the world of Bioinformatics with Machine Learning
https://www.kdnuggets.com/2019/09/explore-world-bioinformatics-machine-learning.html
https://www.kdnuggets.com/2019/09/explore-world-bioinformatics-machine-learning.html
MIDL2020 Paper submission deadline is the end of January! I am an organizer this year! It is going to be great as usual!
The conference has a broad scope including all areas of medical image analysis and computer-assisted intervention where deep learning is a key element.
https://2020.midl.io/call-for-papers.html
The conference has a broad scope including all areas of medical image analysis and computer-assisted intervention where deep learning is a key element.
https://2020.midl.io/call-for-papers.html
Notes on iMAML: Meta-Learning with Implicit Gradients
By Ferenc Huszar : https://www.inference.vc/notes-on-imaml-meta-learning-without-differentiating-through/
#ArtificialIntelligence #MetaLearning #NeuralNetworks
By Ferenc Huszar : https://www.inference.vc/notes-on-imaml-meta-learning-without-differentiating-through/
#ArtificialIntelligence #MetaLearning #NeuralNetworks
inFERENCe
Notes on iMAML: Meta-Learning with Implicit Gradients
This week I read this cool new paper on meta-learning: it a slightly different
approach compared to its predecessors based on some observations about
differentiating the optima of regularized optimization.
* Aravind Rajeswaran, Chelsea Finn, Sham Kakade…
approach compared to its predecessors based on some observations about
differentiating the optima of regularized optimization.
* Aravind Rajeswaran, Chelsea Finn, Sham Kakade…
Implicit Autoencoders
Alireza Makhzani : https://arxiv.org/abs/1805.09804
#DeepLearning #MachineLearning #NeuralNetworks
Alireza Makhzani : https://arxiv.org/abs/1805.09804
#DeepLearning #MachineLearning #NeuralNetworks
arXiv.org
Implicit Autoencoders
In this paper, we describe the "implicit autoencoder" (IAE), a generative
autoencoder in which both the generative path and the recognition path are
parametrized by implicit distributions. We use...
autoencoder in which both the generative path and the recognition path are
parametrized by implicit distributions. We use...
Logarithmic Regret for Online Control
Naman Agarwal, Elad Hazan, Karan Singh : https://arxiv.org/abs/1909.05062
#MachineLearning #Optimization #Control
Naman Agarwal, Elad Hazan, Karan Singh : https://arxiv.org/abs/1909.05062
#MachineLearning #Optimization #Control
arXiv.org
Logarithmic Regret for Online Control
We study optimal regret bounds for control in linear dynamical systems under
adversarially changing strongly convex cost functions, given the knowledge of
transition dynamics. This includes...
adversarially changing strongly convex cost functions, given the knowledge of
transition dynamics. This includes...
Machine Learning Engineer (Research)
Machine Learning Engineer (Research)
Machine Learning Engineers in our research group advance the frontier of what is possible in human-level Information Extraction, by conducting fundamental research in the areas of: natural language understanding, computer vision, representation learning, and knowledge graphs.
@ArtificialIntelligenceArticles
Responsibilities
Improve the accuracy of existing information extraction systems by advancing the current state-of-the-art
Experiment and validate for production new AI capabilities
Publish papers to share new discoveries with AI community
Implement your cutting edge research in the world’s largest production knowledge graph
Collaborate with other Diffbot researchers as well as external AI labs
Requirements
PhD or MS in Computer Science or equivalent work experience
Published research in areas of Web information extraction, natural language processing, computer vision, entity linking, relation extraction, representation learning, deep learning, knowledge inference, and other related fields
Preferred Skills
Programming ability: Java, Python, C++, CUDA
Experience in writing algorithms for speed and scalability
Perks & benefits for this role
Competitive compensation
100% company sponsored medical, dental and vision insurance
401k with company contribution matching
Free lunches, snacks and beverages
Customized computer setup
Unlimited paid time off
Parental leave
Dog friendly office
Commuter benefits
Ongoing learning through mentorship and education budget
Office setting – right next to downtown Menlo Park and CalTrain
Each employee has his/her own office
Onsite gym + fitness classes (Zumba, HIIT, Yoga, Body Sculpt, Muscle Conditioning, Ujam, Core Blast, and Mixed Fit)
Work remotely when needed and work on a flexible schedule
Opt-in team events and get togethers – BBQs, game nights, poker nights, happy hours, hiking and more
Work with an exceptional team of bright, innovative, fun and ambitious individuals from all around the world
To apply, please submit:
A short self-introduction expressing your interest and above qualifications
A resume
https://ai-jobs.net/job/machine-learning-engineer-research/
https://t.iss.one/ArtificialIntelligenceArticles
Machine Learning Engineer (Research)
Machine Learning Engineers in our research group advance the frontier of what is possible in human-level Information Extraction, by conducting fundamental research in the areas of: natural language understanding, computer vision, representation learning, and knowledge graphs.
@ArtificialIntelligenceArticles
Responsibilities
Improve the accuracy of existing information extraction systems by advancing the current state-of-the-art
Experiment and validate for production new AI capabilities
Publish papers to share new discoveries with AI community
Implement your cutting edge research in the world’s largest production knowledge graph
Collaborate with other Diffbot researchers as well as external AI labs
Requirements
PhD or MS in Computer Science or equivalent work experience
Published research in areas of Web information extraction, natural language processing, computer vision, entity linking, relation extraction, representation learning, deep learning, knowledge inference, and other related fields
Preferred Skills
Programming ability: Java, Python, C++, CUDA
Experience in writing algorithms for speed and scalability
Perks & benefits for this role
Competitive compensation
100% company sponsored medical, dental and vision insurance
401k with company contribution matching
Free lunches, snacks and beverages
Customized computer setup
Unlimited paid time off
Parental leave
Dog friendly office
Commuter benefits
Ongoing learning through mentorship and education budget
Office setting – right next to downtown Menlo Park and CalTrain
Each employee has his/her own office
Onsite gym + fitness classes (Zumba, HIIT, Yoga, Body Sculpt, Muscle Conditioning, Ujam, Core Blast, and Mixed Fit)
Work remotely when needed and work on a flexible schedule
Opt-in team events and get togethers – BBQs, game nights, poker nights, happy hours, hiking and more
Work with an exceptional team of bright, innovative, fun and ambitious individuals from all around the world
To apply, please submit:
A short self-introduction expressing your interest and above qualifications
A resume
https://ai-jobs.net/job/machine-learning-engineer-research/
https://t.iss.one/ArtificialIntelligenceArticles
ai-jobs.net
Machine Learning Engineer (Research) | ai-jobs.net
Machine Learning Engineer (Research) Machine Learning Engineers in our research group advance the frontier of what is possible in human-level Information Extraction, by conducting fundamental research in the areas of: natural language understanding, computer…
Machine Learning Researcher / Computational Neuroscientist
https://jobs.apple.com/en-us/details/200104555/machine-learning-researcher-computational-neuroscientist
https://t.iss.one/ArtificialIntelligenceArticles
https://jobs.apple.com/en-us/details/200104555/machine-learning-researcher-computational-neuroscientist
https://t.iss.one/ArtificialIntelligenceArticles
Telegram
ArtificialIntelligenceArticles
for who have a passion for -
1. #ArtificialIntelligence
2. Machine Learning
3. Deep Learning
4. #DataScience
5. #Neuroscience
6. #ResearchPapers
7. Related Courses and Ebooks
1. #ArtificialIntelligence
2. Machine Learning
3. Deep Learning
4. #DataScience
5. #Neuroscience
6. #ResearchPapers
7. Related Courses and Ebooks
Artificial Intelligence Takes On Earthquake Prediction - After successfully predicting laboratory earthquakes, a team of geophysicists has applied a machine learning algorithm to quakes in the Pacific Northwest.
https://www.quantamagazine.org/artificial-intelligence-takes-on-earthquake-prediction-20190919/
https://www.quantamagazine.org/artificial-intelligence-takes-on-earthquake-prediction-20190919/
Quanta Magazine
Artificial Intelligence Takes On Earthquake Prediction
After successfully predicting laboratory earthquakes, a team of geophysicists has applied a machine learning algorithm to quakes in the Pacific Northwest.
"Hierarchical Reinforcement Learning for Open-Domain Dialog"
Abdelrhman Saleh, Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen, Rosalind Picard : https://arxiv.org/abs/1909.07547
Code: https://github.com/natashamjaques/neural_chat
Bots! https://neural.chat/vhrl_techniques/
#MachineLearning #ReinforcementLearning #Transformers
Abdelrhman Saleh, Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen, Rosalind Picard : https://arxiv.org/abs/1909.07547
Code: https://github.com/natashamjaques/neural_chat
Bots! https://neural.chat/vhrl_techniques/
#MachineLearning #ReinforcementLearning #Transformers
Do no harm: a roadmap for responsible machine learning for health care
https://www.nature.com/articles/s41591-019-0548-6
https://www.nature.com/articles/s41591-019-0548-6
Nature
Do no harm: a roadmap for responsible machine learning for health care
Nature Medicine - In this Perspective, the authors present a framework, context and guidelines for accelerating the translation of machine-learning-based interventions in health care.
Deep Learning Pioneer Yoshua Bengio Says AI Is Not Magic And Intel AI Experts Explain Why And How
https://www.forbes.com/sites/gilpress/2019/09/20/deep-learning-pioneer-yoshua-bengio-says-ai-is-not-magic-and-intel-ai-experts-explain-why-and-how/#19bb57b712a6
https://www.forbes.com/sites/gilpress/2019/09/20/deep-learning-pioneer-yoshua-bengio-says-ai-is-not-magic-and-intel-ai-experts-explain-why-and-how/#19bb57b712a6
Forbes
Deep Learning Pioneer Yoshua Bengio Says AI Is Not Magic And Intel AI Experts Explain Why And How
Deep learning pioneer Yoshua Bengio and Intel executives on the present and future of AI
Large e-retailer image dataset for visual search and product classification. https://arxiv.org/abs/1909.08612
The Disruptions of 5G on Data-driven Technologies and Applications. https://arxiv.org/abs/1909.08096
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review. https://arxiv.org/abs/1909.08072
Megatron-LM: Training Multi-Billion Parameter Language Models Using GPU Model Parallelism. https://arxiv.org/abs/1909.08053