
Institute for Pure & Applied Mathematics (IPAM)
The Institute for Pure and Applied Mathematics (IPAM) is a National Science Foundation Math Institute at the University of California, Los Angeles (UCLA) that fosters the interaction of mathematics with a broad range of science and technology, builds new interdisciplinary research communities, promotes mathematical innovation, and engages and transforms the world through mathematics. IPAM fulfills its mission through workshops and programs that connect mathematics and other disciplines or multiple areas of mathematics. These activities bring in thousands of visitors annually from academia, government, and industry. The NSF has encouraged IPAM to make the scientific presentations of our speakers available to a wider audience. While this YouTube channel contains many of our most popular videos, our full video archive is available at www.ipam.ucla.edu/videos.
Episodes


Yusu Wang - Discrete Morse Graph Skeletonization & Application to Local Structures of scRNA-seq Data

Sara Solla - The effect of network connectivity on population neural dynamics - IPAM at UCLA

Smita Krishaswamy - Inferring & Characterizing Neuronal Connectivity w/ deep geometry & topology

Nicole Sanderson - The ABCs of topological data analysis for matrix analysis - IPAM at UCLA

Sung Soo Kim - Visual Processing During Navigation - IPAM at UCLA

Carina Curto - Architectural constraints on recurrent network dynamics - IPAM at UCLA

Julia Brynildsen - The cost of brain state transitions - IPAM at UCLA

Sarah Muldoon - Personalized Brain Network Models Augment Individual Differences - IPAM at UCLA

Gwyneth Card - What do we want to know and how will a connectome help us know it? - IPAM at UCLA

Susanne Schreiber - Beyond classical connectivity: a look at gap junctions and mitochondria

Srini Turaga - How to simulate a connectome? - IPAM at UCLA

Giovanni Petri - Informational and topological signatures of individuality - IPAM at UCLA

Jonathan Rubin - dynamics to constrain connectivity of neuronal population in respiratory brainstem

Moritz Helmstaedter - Analysis of cortical connectomes - IPAM at UCLA

Larry Abbott - Connectome-based modeling in the fly - IPAM at UCLA

Philipp Schlegel - Insights from Comparative Connectomics in Drosophila - IPAM at UCLA

Moo K. Chung - Tutorial: Topological Data Analysis on Dynamic Brain Networks - IPAM at UCLA

Mason A. Porter - Setting the Stage with Networks and Network Dynamics - IPAM at UCLA

Vivek Jayaraman - How connectomes can help us understand navigational attractor dynamics
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