Efficiently measuring a quantum device using machine learning

Lennon et al.: https://arxiv.org/abs/1810.10042

#ArtificialInteligence #QuantumPhysics #Research #Physics #MachineLearning

FishExplorer

1.5 million neurons, cell-level activity during multiple behaviors
15 TB raw, 56 GB compressed
18 fish whole-brain data, ~100k neurons/fish

Data and code: https://github.com/xiuyechen/fishexplorer

Paper:https://www.sciencedirect.com/science/article/pii/S0896627318308444

#bigdata #brain #datascience #machinelearning #research

Efficiently measuring a quantum device using machine learning

paper : https://arxiv.org/abs/1810.10042 #ArtificialInteligence #QuantumPhysics #Research #Physics #MachineLearning

new paper of andrew ng : MRNet: Deep-learning-assisted diagnosis for knee magnetic resonance imaging

In this #research article, Nicholas Bien & coll present an automated system for interpreting knee magnetic resonance images (#MRI) to prioritize high-risk patients and assist clinicians in making diagnoses.

https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002699

https://t.me/ArtificialIntelligenceArticles

Short summaries of #research papers: a great idea!
http://www.shortscience.org

#artificialintelligence #science

Best Paper Awards in Computer Science (since 1996)

A well maintained list: https://jeffhuang.com/best_paper_awards.html

#artificialintelligence #award #machinelearning #papers #research @ArtificialIntelligenceArticles

The field of #machinelearning seeks to answer the question "How can we build computer systems that automatically improve with experience, and what are the fundamental laws that govern all learning processes?," Tom Mitchell on the Discipline of Machine Learning

Story: https://mld.ai/6b76a
Paper: http://www.cs.cmu.edu/~tom/pubs/MachineLearning.pdf

#ML #artificialintelligence #research #carnegiemellon #scsatcmu [ machine learning ] [ artificial intelligence ] #AI #education

MineRL Competition 2019

Competition Overview: http://minerl.io/competition/

#artificialintelligence #deeplearning #reinforcementlearning #research #technology

"Training Neural Nets on Larger Batches: Practical Tips for 1-GPU, Multi-GPU & Distributed setups"
By Thomas Wolf: https://medium.com/huggingface/training-larger-batches-practical-tips-on-1-gpu-multi-gpu-distributed-setups-ec88c3e51255
#ArtificialInteligence #DeepLearning #MachineLearning #NeuralNetworks #Research

Ford government slashes funding to research institutes focused on artificial intelligence
By Kate Allen:
https://www.thestar.com/news/gta/2019/05/19/ford-government-slashes-funding-to-research-institutes-focused-on-artificial-intelligence.html https://t.me/ArtificialIntelligenceArticles
#ArtificialIntelligence #Ontario #Canada #Research

The Best and Most Current of Modern Natural Language Processing
Blog by Victor Sanh: https://medium.com/huggingface/the-best-and-most-current-of-modern-natural-language-processing-5055f409a1d1
#NaturalLanguageProcessing #MachineLearning #NLP #DeepLearning #Research

Minister Bains announces investment to accelerate medical breakthroughs that will enable truly personalized health care
“This investment promises not only to improve the future of Canadians’ health but also to do it with made-in-Canada solutions. By harnessing Canada’s strengths in health research and AI, we’re helping to usher in a new era of more personalized care that will mean better health outcomes. We’re excited to see all the new health and biosciences innovations that will result from this collaboration.” – The Honourable Navdeep Bains, Minister of Innovation, Science and Economic Development
From: Innovation, Science and Economic Development Canada https://www.canada.ca/en/innovation-science-economic-development/news/2019/05/minister-bains-announces-investment-to-accelerate-medical-breakthroughs-that-will-enable-truly-personalized-health-care.html
#artificialintelligence #canada #health #innovation #research

Towards Reproducible Research with PyTorch Hub
Blog by Team PyTorch: https://pytorch.org/blog/towards-reproducible-research-with-pytorch-hub/
#deeplearning #pytorch #research

Towards Reproducible Research with "PyTorch Hub"

By Team PyTorch : https://pytorch.org/blog/towards-reproducible-research-with-pytorch-hub/

#deeplearning #pytorch #research

"Rapid research framework for PyTorch. The researcher's version of Keras"

GitHub, by William Falcon : https://github.com/williamFalcon/pytorch-lightning

#deeplearning #pytorch #research

TRFL (pronounced "truffle"): a library of reinforcement learning building blocks
By the Research Engineering team at DeepMind: https://github.com/deepmind/trfl
#reinforcementlearning #research #deeplearning

Carnegie Mellon University, Accepted Papers at NeurIPS 2019

Learn more → https://mld.ai/neurips2019

#NeurIPS2019 #NeurIPS #MachineLearning #ML #ComputationalNeuroscience #Research #CarnegieMellon #CMUAI #mldcmu

ns3-gym: Extending OpenAI Gym for Networking Research
Piotr Gawłowicz and Anatolij Zubow : https://arxiv.org/abs/1810.03943
#OpenAIGym #Networking #Research

We have a lot to thank neurobiologists and neuroscientists for the #deeplearning revolution. A LOT!

In my lectures about #computervision you've heard me talk about the famous cat experiment by Torsten Wiesel and David Hubel.

Here they are with Stephen Kuffler (left) at the Department of Neurobiology at Harvard Medical School which was founded in 1966.

Source: Harvard Medical School.
PS: My 10 min lectures will go a bit into detail about the experiments and what they mean.
#artificiallintelligence #aiplaybook #research