Teaching a neural network to use a calculator
Blog by Reiichiro Nakano : https://reiinakano.com/2019/11/12/solving-probability.html
#ArtificialIntelligence #DeepLearning #MachineLearning

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Geoffrey Hinton interview

How to Read Articles That Use Machine Learning
Users’ Guides to the Medical Literature

https://jamanetwork.com/journals/jama/article-abstract/2754798

Geometry-Aware Neural Rendering

Josh Tobin, OpenAI Robotics, Pieter Abbeel : https://arxiv.org/abs/1911.04554

#DeepLearning #MachineLearning #NeurIPS2019

"SEMINAL DEBATE : Yoshua Bengio | Gary Marcus"
This Is The Debate The AI World Has Been Waiting For
LIVE STREAMING : https://bengio-marcus.eventbrite.ca
Date and Time : December 23, 2019 | 7:00 PM – 8:30 PM EST
#ArtificialIntelligence #Debate

Scientists have found that a drug called rapamycin can help prevent dementia by restoring blood flow to the brain that is lost during aging.
https://www.labroots.com/trending/cell-and-molecular-biology/16097/rapamycin-prevent-age-related-memory-loss-cerebral-blood-flow

"Gatsby Unit PhD: Training in theoretical and computational neuroscience and machine learning.

Deadline: 17th November 2019

The Gatsby Computational Neuroscience Unit is a leading research centre focused on theoretical neuroscience and machine learning. We study unsupervised, supervised and reinforcement learning in brains and machines; inference, coding and neural dynamics; Bayesian and kernel methods, and deep learning; with applications to the analysis of perceptual processing and cognition, neural data, signal and image processing, machine vision, network data and nonparametric hypothesis testing.

The Unit provides a unique opportunity for a critical mass of theoreticians to interact closely with each other, with the Sainsbury Wellcome Centre for Neural Circuits and Behaviour (SWC, with which we share a purpose-designed building), with the cross-faculty Centre for Computational Statistics and Machine Learning (CSML), and with other world-class research groups in related departments at UCL including: Computer Science; Functional Imaging; Neuroscience, Physiology and Pharmacology; Psychology; Neurology; Ophthalmology; The Ear Institute; Statistical Science; and the nearby Alan Turing and Francis Crick Institutes.

Students at the Gatsby Unit complete a four-year PhD in either machine learning or theoretical neuroscience, with minor emphasis in the complementary field. Courses in the first year, taught in conjunction with colleagues from the SWC and CSML, provide a comprehensive and intensive introduction to both fields. Students are encouraged to work and interact closely with peers and faculty in the SWC and/or CSML throughout their PhD, providing a uniquely multidisciplinary research environment.

Applicants should have a strong analytical and quantitative background, a keen interest in neuroscience, machine learning or both, and a relevant first degree, for example in Computer Science, Engineering, Mathematics, Neuroscience, Physics, Psychology or Statistics.

Full funding is available regardless of nationality and current residence. The Unit also welcomes applicants who have secured or are seeking funding from other sources.

Applications (including a CV, transcripts, statement of research interests, and letters from three referees) should be sent directly to [email protected]. Only applications complete by the deadline are guaranteed full consideration; late applications will be entertained only if places remain unfilled.

For further details of our programme and how to apply please see:
https://www.gatsby.ucl.ac.uk/teaching/phd
Further details of research interests are available from
https://www.gatsby.ucl.ac.uk/research.html
and the individual faculty webpages at
https://www.gatsby.ucl.ac.uk/Members.html."

Self-training with Noisy Student improves ImageNet classification
https://arxiv.org/abs/1911.04252

Some investigators have argued that emotions, especially animal emotions, are illusory concepts outside the realm of scientific inquiry. However, with advances in neurobiology and neuroscience, researchers are demonstrating that this position is wrong as they move closer to a lasting understanding of the biology and psychology of emotion. In Affective Neuroscience, Jaak Panksepp provides the most up-to-date information about the brain-operating systems that organize the fundamental emotional tendencies of all mammals. Presenting complex material in a readable manner, the book offers a comprehensive summary of the fundamental neural sources of human and animal feelings, as well as a conceptual framework for studying emotional systems of the brain. Panksepp approaches emotions from the perspective of basic emotion theory but does not fail to address the complex issues raised by constructionist approaches. These issues include relations to human consciousness and the psychiatric implications of this knowledge. The book includes chapters on sleep and arousal, pleasure and fear systems, the sources of rage and anger, and the neural control of sexuality, as well as the more subtle emotions related to maternal care, social loss, and playfulness. Representing a synthetic integration of vast amounts of neurobehavioral knowledge, including relevant neuroanatomy, neurophysiology, and neurochemistry, this book will be one of the most important contributions to understanding the biology of emotions since Darwins The Expression of the Emotions in Man and Animals.