• Convolutional Dictionary Learning for Tomographic Reconstruction (Cristina Garcia-Cardona, LANL)

    Argue Auditorium, Pomona College 610 N. College Ave., Claremont, CA, United States

    Convolutional sparse representation is an efficient tool for computing sparse representations for entire signals in terms of sums of a set of convolutions with dictionary filters. Unlike representations that are based on overlapping image patches, the convolutional representation optimizes over the entire image, yielding representations that are very sparse both spatially and across the filters. […]

  • CCMS Field Committee Meeting

    Shanahan B460, Harvey Mudd College 301 Platt Blvd., Claremont, CA, United States

    The Field Committee Meeting is our chance to socialize with our colleagues and coordinate our course offerings for the coming academic year (2019-2020). Please come to discuss course offerings and other synergistic items. Refreshments at 4:00, meeting at 4:15.

  • Mathematics: Pure, Applied, A Liberal Art ( Al Erisman, Seattle Pacific University)

    Shanahan B460, Harvey Mudd College 301 Platt Blvd., Claremont, CA, United States

    From the view of a pure mathematician, those working in pure mathematics produce pure knowledge. Whether used or not, it has a great elegance and value in and of itself. Those in applied mathematics simply pick up what has been done and use it in designing or building things. Number theory is often used to […]

  • Algebraic and Polyhedral Perspectives on Combinatorial Neural Codes (Robert Davis, Harvey Mudd)

    Shanahan B460, Harvey Mudd College 301 Platt Blvd., Claremont, CA, United States

    In the 1970s, James O’Keefe and his team observed that certain neurons in the brain, called place cells, spike in their firing rates when the animal is in a particular physical location within its arena. If a place cell is thought of as either “active” or “silent,” then one may represent the co-firing patterns of […]

  • Cracking the Code: Predicting Properties of Material Fracture Networks using Machine Learning (Allon Percus, CGU)

    Shanahan B460, Harvey Mudd College 301 Platt Blvd., Claremont, CA, United States

    Understanding how fluid flows through heterogeneous materials, and how it can make these materials fail, are among the hardest challenges in materials science.  Experiments and simulations show that flow through subsurface rock is mostly limited to a small subnetwork, or backbone, of fractures.  Identifying this backbone would allow for a large speedup in flow and […]

  • Personal Perspectives on m-ary Partitions (James Sellers, Penn State)

    Shanahan B460, Harvey Mudd College 301 Platt Blvd., Claremont, CA, United States

    Abstract:  A great deal of my research journey has involved the study of m-ary partitions.  These are integer partitions wherein each part must be a power of a fixed integer m > […]

  • Accidental Mathematics (Matt Stamps, Yale-NUs College)

    Shanahan B460, Harvey Mudd College 301 Platt Blvd., Claremont, CA, United States

    Abstract:  Growing up, I always loved learning about world-changing scientific breakthroughs that were discovered by accident.  Penicillin, artificial sweeteners, X-rays, and synthetic dyes are just a few of the discoveries […]

  • Some Unexpected Mathematics Arising From Research at NIST ( Hunt, NIST)

    Shanahan B460, Harvey Mudd College 301 Platt Blvd., Claremont, CA, United States

    A lot of the mathematics done at NIST supports the research on and measurement of advanced materials and technology. In this rather applied context. surprising mathematics makes an appearance. We […]