In this lecture, Dan Littman will describe how intestinal commensal bacteria shape functions of immune system cells that prevent invasion by pathogenic microbes but can also contribute to systemic inflammation.
In this lecture, Mauro Maggioni will discuss a family of ideas, algorithms and results for learning from high-dimensional data.
MEG and EEG Signals and Their Sources: Insights from Physics, Physiology and Anatomy Matti Hamalainen, Massachusetts General Hospital Understanding the biophysics and physiology underlying the generation of detectable extracranial magnetic fields and electric potentials is of prime importance for correct interpretation of magnetoencephalography (MEG) and electroencephalography (EEG) data. Matti Hamalainen will discuss the neural sources of...
In this talk, Christian Borgs will give an introduction to belief propagation, discuss how the accuracy of belief propagation has been rigorously established, and present recent applications to systems biology.
A day to explore Maxim Kontsevich's contributions to the field of mathematics.
Topology, the "rubber sheet geometry", studies properties that do not change when objects are pulled and stretched. Accepting somewhat fuzzy input, it is the part of mathematics typically applied when qualitative conclusions are reached. However, it has a quantitative aspect important in understanding singularities, and potentially, high-dimensional noisy data and aspects of large-scale geometry of networks. Prof. Weinberger will discuss a variety of phenomena that arise or are illuminated by tracking of the complexity of geometric constructions.
Basic motor skills such as looking, reaching and walking do not simply appear as the result of maturation. Rather, infants must learn to move. Learning entails discovering new forms of movements to suit the task at hand and using perceptual information to select and modify movements adaptively.
Basic motor skills such as looking, reaching and walking do not simply appear as the result of maturation. Rather, infants must learn to move. Learning entails discovering new forms of movements to suit the task at hand and using perceptual information to select and modify movements adaptively.
Since at least the time when it was understood that the circumference of a circle is pi multiplied by its diameter, the applications of mathematics have raced on far ahead of the foundations of the subject itself. By considering a variety of examples, principally from the 19th century, we will explore the tension between mathematics and its applications, and reasons why it remains a valuable and rewarding occupation to develop the necessary framework for existing and “well understood” theories.
Speakers: Jonathan Simon, University of Maryland Timothy Roberts, Children's Hospital of Philadelphia Jonathan Winawer, New York University https://vimeo.com/117625451 Signal Analysis Primer and Applications Jonathan Z. Simon, University of Maryland Modern cognitive neuroscientists using electrocorticography (ECoG), MEG and electroencephalography (EEG) are under substantial pressure to use advanced signal processing and analysis techniques, but typically receive...
