Flatiron Internal Conference: Flatiron-wide Algorithms and Mathematics

Speaker List

• Joakim Andén
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    Wavelets

• Alex Barnett
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    Introduction to interpolation, integration and spectral methods

• Megan Bedell (CCA)
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    Research Applications of Optimization: Data-Driven Spectroscopy

• Keaton Burns
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    Overview of various methods to solve differential equations

• Giuseppe Carleo
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    Deep Generative Modeling for Statistical and Quantum Physics

• Mitya Chklovskii
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    Biological neural network algorithms

• Gabriella Contardo
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    Introduction to Deep Learning

• Emily Cunningham (CCA)
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    Hierarchical Modeling and Stellar Velocities

• Dan Foreman-Mackey
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    Introduction to Markov chain Monte Carlo

• Johannes Friedrich
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    The why and how of nonnegative matrix factorization

• Mariano Gabitto
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    Scalable Bayesian Inference.

• Leslie Greengard
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    A practical introduction to adjoint methods

• Elad Hazan
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    Tutorial: Optimization for Machine Learning

• Shirley Ho
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    Introduction to Deep Learning

• Katherine Hyatt
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    Introduction to Tensor Network Methods

• Laurence Levasseur
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    Uncertainty Estimation with Neural Networks

• Jeremy Magland
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    Clustering in low dimensions

• Christian Mueller
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    Optimization landscapes - a gentle multi-disciplinary introduction to optimization

• Eftychios Pnevmatikakis (CCM)
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    Randomized linear algebra and matrix approximation

• Manas Rachh
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    Fast algorithms for hierarchically structured matrices

• Michael Shelley
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    PDEs: The long and the short.

• Marina Spivak
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    Spectral Clustering and Dimensionality Reduction

• Jun Wang
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    Introduction to Integral Equation Methods

• Shiwei Zhang
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    The quantum-ness in quantum Monte Carlo: mathematical and algorithmic implications