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Pacific Northwest Seminar on Topology, Algebra, and Geometry in Data Science
Past Events
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Global optimization of analytic functions over compact domain (Georgy Scholten, Sorbonne Université) -
November 7, 2023
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Towards a deeper theoretical understanding of neural networks (Lechao Xiao, Google Brain) -
February 16, 2023
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A gradient sampling method with complexity guarantees for Lipschitz functions in high and low dimensions (Swati Padmanabhan, UW) -
February 9, 2023
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What can adversarial examples tell us about similarities between neural networks? (Jacob Springer, Carnegie Mellon University) -
February 2, 2023
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Computing Representations for Lie Algebraic Networks (Noah Shutty, Google) -
January 26, 2023
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projUNN: efficient method for training deep networks with unitary matrices (Bobak Kiani (MIT)) -
October 27, 2022
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Neural Networks with Learned Coarsening for Simplicial Complexes (Sarah McGuire (Michigan State University)) -
October 13, 2022
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The Intrinsic Manifolds of Radiological Images and Their Role in Deep Learning (Nick Konz (Duke)) -
October 6, 2022
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Groups and Symmetries in Statistical Models (Anna Seigal (Harvard)) -
May 26, 2022
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How to choose informative representations of topological features in persistent homology (Gregory Henselman-Petrusek (PNNL)) -
May 19, 2022
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Approximate vector bundles and fiberwise dimensionality reduction (Luis Scoccola (Northeastern)) -
May 5, 2022
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Modeling Many-to-Many Maps (Lizzy Coda (PNNL)) -
April 28, 2022
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Riemannian Geometry in Machine Learning (Isay Katsman (Cornell)) -
April 21, 2022
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Towards Mechanics of Learning in Neural Networks (Daniel Kunin (Stanford) and Hidenori Tanaka (NTT Physics & Informatics Laboratories)) -
April 14, 2022
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Machine Learning Beyond Accuracy (Shibani Santurkar (Stanford)) -
April 7, 2022
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Functional dimension of feedforward ReLU neural networks (Kathryn Lindsey, (Boston College)) -
February 10, 2022
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Applications of Group Symmetry (Emily King, (Colorado State University)) -
February 3, 2022
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DNA: Dynamic Network Augmentation (Scott Mahan (University of California, San Diego)) -
January 27, 2022
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A tool for deep learning model interpretability (Davis Brown (Pacific Northwest National Laboratory)) -
January 20, 2022
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From Zigzags to Networks: Topological Tools for Time Series Analysis (Sarah Tymochko (Michigan State University)) -
January 13, 2022
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Private AI: Machine Learning on Encrypted Data (Kristin Lauter, Facebook AI Research (FAIR)) -
December 2, 2021
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TBA (Mitchell Wortsman, UW CSE) -
November 18, 2021
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Chirality in Vision (Rekha Thomas, UW Math) -
November 12, 2021
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Detecting Short-lasting Topics Using Nonnegative Tensor Decomposition ( Lara Kassab, Colorado State University) -
November 4, 2021
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Using the linear geometry of ReLU neural networks to detect out-of-distribution inputs (Grayson Jorgenson, Pacific Northwest National Lab) -
October 28, 2021
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Studying relations geometrically and topologically (Michael Robinson, American University) -
October 21, 2021
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A Polynomial Time Algorithm for Constructing Equivariant Neural Networks (Marc Finzi, NYU) -
October 14, 2021
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Topic Models, Methods, and Medicine (Jamie Haddock, Harvey Mudd College) -
October 7, 2021