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The Deep Learning Revolution
How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of...
Unsupervised Learning
Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.
The Computational Brain
"The Computational Brain addresses a broad audience: neuroscientists, computer scientists, cognitive scientists, and philosophers. It is written for both the expert and novice. A basic overview of neuroscience and computational theory is provided, followed by a study of some of the most recent and sophisticated modeling work in the context of relevant neurobiological research. Technical terms are clearly explained in the text, and definitions are provided in an extensive glossary. The appendix contains a précis of neurobiological techniques."--Jacket.
The Deep Learning Revolution
How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of...
Liars, Lovers, and Heroes
This book combines cutting-edge findings in neuroscience with examples from history and the headlines to introduce the new science of cultural biology, born of advances in brain imaging, computer modeling, and genetics. Doctors Quartz and Sejnowski show how both our noblest and darkest traits are rooted in brain systems so ancient that we share them with insects. They then demystify the dynamic engagement between brain and world that makes us something far beyond the sum of our parts. The authors show how our humanity unfolds in precise stages as brain and world engage on increasingly complex levels. Their discussion embraces shaping forces as ancient as climate change over millennia and events as recent as the terrorism and heroism of September 11, and offers intriguing answers to some of our most enduring questions, including why we live together, love, kill -- and sometimes lay down our lives for others.
The Neocortex
Experts review the latest research on the neocortex and consider potential directions for future research. Over the past decade, technological advances have dramatically increased information on the structural and functional organization of the brain, especially the cerebral cortex. This explosion of data has radically expanded our ability to characterize neural circuits and intervene at increasingly higher resolutions, but it is unclear how this has informed our understanding of underlying mechanisms and processes. In search of a conceptual framework to guide future research, leading researchers address in this volume the evolution and ontogenetic development of cortical structures, the cor...
Neural Codes and Distributed Representations
Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. The present volume focuses on neural codes and representations, topics of broad interest to neuroscientists and modelers. The topics addressed are: how neurons encode information through action potential firing patterns, how populations of neurons represent information, and how individual neurons use dendritic processing and biophysical properties of synapses to decode spike trains. The papers encompass a wide range of levels of investigation, from dendrites and neurons to networks and systems.
Uncommon Sense Teaching
Top 10 Pick for Learning Ladders’ Best Books for Educators Summer 2021 A groundbreaking guide to improve teaching based on the latest research in neuroscience, from the bestselling author of A Mind for Numbers. Neuroscientists and cognitive scientists have made enormous strides in understanding the brain and how we learn, but little of that insight has filtered down to the way teachers teach. Uncommon Sense Teaching applies this research to the classroom for teachers, parents, and anyone interested in improving education. Topics include: • keeping students motivated and engaged, especially with online learning • helping students remember information long-term, so it isn't immediately forgotten after a test • how to teach inclusively in a diverse classroom where students have a wide range of abilities Drawing on research findings as well as the authors' combined decades of experience in the classroom, Uncommon Sense Teaching equips readers with the tools to enhance their teaching, whether they're seasoned professionals or parents trying to offer extra support for their children's education.
Talking Nets
Surprising tales from the scientists who first learned how to use computers to understand the workings of the human brain. Since World War II, a group of scientists has been attempting to understand the human nervous system and to build computer systems that emulate the brain's abilities. Many of the early workers in this field of neural networks came from cybernetics; others came from neuroscience, physics, electrical engineering, mathematics, psychology, even economics. In this collection of interviews, those who helped to shape the field share their childhood memories, their influences, how they became interested in neural networks, and what they see as its future. The subjects tell stori...
Bayesian Brain
Experimental and theoretical neuroscientists use Bayesian approaches to analyze the brain mechanisms of perception, decision-making, and motor control.
