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Institute for Pure & Applied Mathematics (IPAM) ยท Science

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

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Nikolaus Grigorieff - Detecting 60S Ribosome Maturation Intermediates in Cells by 2D Template Match

16 Nov 2022
44m
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Serena Yeung - Computer Vision for Segmenting & Analyzing Subcellular Components in CE Tomography

16 Nov 2022
54m
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Katerina Naydenova - Molecular structure extrapolation to zero dose with cryoEM - IPAM at UCLA

15 Nov 2022
43m
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Petar Petrov - Laser phase-contrast transmission electron microscopy & computational opportunities

15 Nov 2022
48m
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Chris Russo - Potential electron cryomicroscopy in situ: technology to identify molecules in cells

15 Nov 2022
40m
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Roy Lederman - Approaches for Exploring the Geometry of Molecular Conformations in Cryo-EM

15 Nov 2022
43m
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Ellen Zhoung - Machine learning for determining protein structure and dynamics from cryo-EM images

15 Nov 2022
48m
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Geoffrey Woollard - Stochastic inference and Computational Optimal Transport in 3D heterogeneity

14 Nov 2022
45m
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Carlos Oscar Sorzano - Machine learning for Single Particle Analysis by Cryo-Electron Microscopy

14 Nov 2022
40m
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Steven Ludtke - Contextual Conformational Variability in CryoEM and CryoET using Deep Learning

14 Nov 2022
41m
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Yimo Han - Assisting 4D-STEM data processing by machine learning and Bayesian optimization

28 Oct 2022
52m
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Peng Wang - Electron Ptychography: Emerging Computational Microscopy for Physical/Biological Science

28 Oct 2022
49m
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Andrew Maiden - Ptychographic imaging via set projection algorithms - IPAM at UCLA

28 Oct 2022
51m
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Sandra van Aert - 3D atomic resolution through dose-efficient fusion of image & analytical technique

28 Oct 2022
32m
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Emilie Ringe - Electron and optical microscopy of magnesium nanoparticles - IPAM at UCLA

27 Oct 2022
48m
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Soledad Villar - Introduction to equivariant machine learning - IPAM at UCLA

27 Oct 2022
46m
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Yonina Eldar - Model Based Deep Learning with Application to Super Resolution - IPAM at UCLA

27 Oct 2022
47m
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Yongsoo Yang - Neural network-assisted atomic electron tomography - IPAM at UCLA

27 Oct 2022
47m
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Emily King - PCA is not dead: Vectorized persistent homology and flag medians - IPAM at UCLA

27 Oct 2022
50m
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Ross Harder - Bragg Coherent Diffraction Imaging at the Advanced Photon Source 34-ID Beamline

26 Oct 2022
36m
Page 60

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