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                        <h1 class="brand-heading">LANE McINTOSH</h1>
                        <p class="intro-text">Bringing insights from the brain to machine learning.<br>Theoretical neuroscientist at Stanford.</p>
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                <h2>About Me</h2>
								<p class="large intro-p">
								In a fraction of a second our brain captures information about our world and effortlessly extracts meaning from this sensory information. 
								What exactly are the computations these neural circuits are performing? 
								Are there general principles for understanding how neural systems are processing information, given the input statistics for instance?
								And can the answers to these questions inform how we build artificially intelligent systems like deep learning networks?
								</p>
								<p class="large intro-p">
								I am a PhD candidate at <a href="http://www.stanford.edu">Stanford</a> where I do a mix of theory and experimental tests of theory in order to get at these questions.
								My PhD research focuses on predictive inference and coding in the early stages of vision, and brings together tools from machine learning, information theory, high-dimensional data analysis, and nonequilibrium physics.
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                <p><a href="mailto:<EMAIL>">lmcintosh (at) stanford.edu</a>
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										<a href="https://www.kaggle.com/lanemcintosh" class="btn btn-default btn-lg"><i class="fa fa-terminal fa-fw"></i> <span class="network-name">Kaggle</span></a>
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<commit_msg>flipped order of headshot and download cv button<commit_after><!DOCTYPE html>
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                        <h1 class="brand-heading"><NAME></h1>
                        <p class="intro-text">Bringing insights from the brain to machine learning.<br>Theoretical neuroscientist at Stanford.</p>
                        <a href="#about" class="btn btn-circle page-scroll">
                            <i class="fa fa-angle-double-down animated"></i>
                        </a>
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                <h2>About Me</h2>
								<p class="large intro-p">
								In a fraction of a second our brain captures information about our world and effortlessly extracts meaning from this sensory information. 
								What exactly are the computations these neural circuits are performing? 
								Are there general principles for understanding how neural systems are processing information, given the input statistics for instance?
								And can the answers to these questions inform how we build artificially intelligent systems like deep learning networks?
								</p>
								<p class="large intro-p">
								I am a PhD candidate at <a href="http://www.stanford.edu">Stanford</a> where I do a mix of theory and experimental tests of theory in order to get at these questions.
								My PhD research focuses on predictive inference and coding in the early stages of vision, and brings together tools from machine learning, information theory, high-dimensional data analysis, and nonequilibrium physics.
								</p>
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                <p><a href="mailto:<EMAIL>">lmcintosh (at) stanford.edu</a>
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										<a href="https://www.kaggle.com/lanemcintosh" class="btn btn-default btn-lg"><i class="fa fa-terminal fa-fw"></i> <span class="network-name">Kaggle</span></a>
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