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Inverse Problems with Symmetry: A Functional Perspective on Multi-Reference...

Anna Little

University of Utah

March 2, 2026 • 12:00 AM

Bayesian Inverse Problems and UQ

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Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting

Nikola Kovachki

NVIDIA Research

March 2, 2026 • 12:00 AM

Bayesian Inverse Problems and UQ

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Structured Matrix Approximations via Tensor Decompositions

Misha Kilmer

Tufts University

February 6, 2026 • 12:00 AM

Randomized Numerical Linear Algebra

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The Polar Express: Optimal Matrix Sign Methods and Their Application to the...

Robert Gower

Flatiron Institute

February 6, 2026 • 12:00 AM

Randomized Numerical Linear Algebra

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Tight Sampling Bounds for Eigenvalue Approximation

David Woodruff

Carnegie Mellon University

February 6, 2026 • 12:00 AM

Randomized Numerical Linear Algebra

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Everything is Vecchia: Unifying low-rank and sparse inverse approximations

Robert Webber

UC San Diego

February 5, 2026 • 12:00 AM

Randomized Numerical Linear Algebra

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An adaptive randomized pivoting strategy for low-rank approximation

Alice Cortinovis

University of Pisa

February 5, 2026 • 12:00 AM

Randomized Numerical Linear Algebra

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Preconditioning without a preconditioner using block Krylov subspace method...

Tyler Chen

JPMorganChase

February 5, 2026 • 12:00 AM

Randomized Numerical Linear Algebra

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Closing the Theory-Practice Gap in Oblivious Subspace Embeddings

Michal Dereziński

University of Michigan

February 5, 2026 • 12:00 AM

Randomized Numerical Linear Algebra

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Estimating a matrix's singular values with interpolative decompositions

Alex Townsend

Cornell University

February 5, 2026 • 12:00 AM

Randomized Numerical Linear Algebra

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Importance Sampling for Nonlinear Models

Fred Roosta

University of Queensland

February 5, 2026 • 12:00 AM

Randomized Numerical Linear Algebra

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Structured Matrix Learning from Matrix-Vector Products

Chris Musco

New York University

February 4, 2026 • 12:00 AM

Randomized Numerical Linear Algebra

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Video Archive

Inverse Problems with Symmetry: A Functional Perspective on Multi-Reference...

Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting

Structured Matrix Approximations via Tensor Decompositions

The Polar Express: Optimal Matrix Sign Methods and Their Application to the...

Tight Sampling Bounds for Eigenvalue Approximation

Everything is Vecchia: Unifying low-rank and sparse inverse approximations

An adaptive randomized pivoting strategy for low-rank approximation

Preconditioning without a preconditioner using block Krylov subspace method...

Closing the Theory-Practice Gap in Oblivious Subspace Embeddings

Estimating a matrix's singular values with interpolative decompositions

Importance Sampling for Nonlinear Models

Structured Matrix Learning from Matrix-Vector Products

Video Archive

Inverse Problems with Symmetry: A Functional Perspective on Multi-Reference...

Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting

Structured Matrix Approximations via Tensor Decompositions

The Polar Express: Optimal Matrix Sign Methods and Their Application to the...

Tight Sampling Bounds for Eigenvalue Approximation

Everything is Vecchia: Unifying low-rank and sparse inverse approximations

An adaptive randomized pivoting strategy for low-rank approximation

Preconditioning without a preconditioner using block Krylov subspace method...

Closing the Theory-Practice Gap in Oblivious Subspace Embeddings

Estimating a matrix's singular values with interpolative decompositions

Importance Sampling for Nonlinear Models

Structured Matrix Learning from Matrix-Vector Products