THE AMALGAMATION OF DATA SCIENCE AND NEUROSCIENCE
https://www.analyticsinsight.net/the-amalgamation-of-data-science-and-neuroscience/

Neural Data Server: A Large-Scale Search Engine for Transfer Learning Data. https://arxiv.org/abs/2001.02799

Lifted Hybrid Variational Inference. https://arxiv.org/abs/2001.02773

Named-Entity-Recognition-NER-Papers
By Pengfei Liu, Jinlan Fu and other contributors: https://github.com/pfliu-nlp/Named-Entity-Recognition-NER-Papers
An elaborate and exhaustive paper list for Named Entity Recognition (NER), covering papers from seven top conferences (ACL / EMNLP / NAACL / Coling / ICLR / AAAI / IJCAI) and eight years (2013-2020).
#ArtificialIntelligence #DeepLearning #MachineLearning

Summary: A new convolutional neural network that utilizes MRI brain scans can forecast genetic mutations in glioma brain tumors.
Source: Osaka University
Researchers at Osaka University have developed a computer method that uses magnetic resonance imaging (MRI) and machine learning to rapidly forecast genetic mutations in glioma tumors, which occur in the brain or spine. The work may help glioma patients to receive more suitable treatment faster, giving better outcomes. The research was recently published in Scientific Reports.
https://neurosciencenews.com/genetics-brain-tumors-15451/

Detection of anaemia from retinal fundus images via deep learning https://www.nature.com/articles/s41551-019-0487-z.epdf?shared_access_token=BcBD1jh7EFkbhRR7GO7epNRgN0jAjWel9jnR3ZoTv0PM60VmCAPkIZuQsecTYZaovpLrjs4HpzIZT_r4kkYc5fNlZWatHh0N1icwpncYARKL54pqNmeNIjwcQ2eQ63-__htO1uHXwZ7GinlLrmJhhQ%3D%3D

Synthesising photo realistic images using GANs (SPADE Method). For more details refer to the original paper presented in CVPR 2019: https://arxiv.org/abs/1903.07291

Explaining the Explainer: A First Theoretical Analysis of LIME
Damien Garreau, Ulrike von Luxburg : https://arxiv.org/abs/2001.03447
#ArtificialIntelligence #DeepLearning #MachineLearning

DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection
Github: https://github.com/EndlessSora/DeeperForensics-1.0
Paper: https://arxiv.org/abs/2001.03024v1
Project Page: https://liming-jiang.com/projects/DrF1/DrF1.html
Video: https://youtu.be/b6iKqkJht38

Can an #AI deep neural network be trained to diagnose low blood sugar from the ECG signal?
https://go.nature.com/2NrqzxM

Fingerpicks are never pleasant and in some circumstances are particularly cumbersome. Taking fingerpick during the night certainly is unpleasant, especially for patients in paediatric age.

"Our innovation consisted in using artificial intelligence for automatic detecting hypoglycaemia via few ECG beats. This is relevant because ECG can be detected in any circumstance, including sleeping."
https://m.medicalxpress.com/news/2020-01-ai-glucose-ecg-fingerprick.html

A marriage of microscopy and machine learning
https://www.broadinstitute.org/news/marriage-microscopy-and-machine-learning

Father of Back propagation
https://dev.to/jithendrabsy/father-of-back-propagation-413f

A scalable pipeline for designing reconfigurable organisms
Kriegman et al.: https://www.pnas.org/content/early/2020/01/07/1910837117
#EvolutionaryComputation #ArtificialLife #Bioengineering

Choosing the Sample with Lowest Loss makes SGD Robust

https://arxiv.org/abs/2001.03316

PyTorch implementation of Meta Sequence-to-Sequence Learning
Github: https://github.com/facebookresearch/meta_seq2seq
Paper: https://cims.nyu.edu/~brenden/papers/Lake2019NeurIPS.pdf
Referred Tutorial: https://github.com/spro/practical-pytorch/blob/master/seq2seq-translation/seq2seq-translation-batched.ipynb

Deep Plastic Surgery: Robust and Controllable Image Editing with Human-Drawn Sketches
Yang et al.: https://arxiv.org/abs/2001.02890
#ArtificialIntelligence #DeepLearning #MachineLearning

Numenta Research Meeting - Geoff Hinton 1981 Paper reviews

https://www.youtube.com/watch?v=sq-BitMGgtc

Geoffrey Hinton Capsule theory

https://www.youtube.com/watch?v=6S1_WqE55UQ