Search for tag: "mcqmc"

Pierre L'Ecuyer Quasi-Monte Carlo for Density Estimation (MCQMC 2020)

Pierre L'Ecuyer Quasi-Monte Carlo for Density Estimation

From  Liam Holligan 0 likes 90 plays 0  

Close of MCQMC 20202 Conference, Mike Giles (University of Oxford)

Mike Giles, University of Oxford

From  Liam Holligan 0 likes 51 plays 0  

Claudia Schillings, University of Mannheim - Optimization approaches for Bayesian inverse problems: Preconditioning integration methods in the small noise or large data limit (MCQMC 2020)

Claudia Schillings, University of Mannheim Optimization approaches for Bayesian inverse problems: Preconditioning integration methods in the small noise or large data limit

From  Liam Holligan 0 likes 63 plays 0  

Peter Kritzer, RICAM Linz - Exponential tractability (MCQMC 2020)

Peter Kritzer, RICAM Linz Exponential tractability

From  Liam Holligan 0 likes 55 plays 0  

Thomas Muller, NVIDIA Variance Reduction using Neural Networks (MCQMC 2020)

Thomas Muller, NVIDIA Variance Reduction using Neural Networks

From  Liam Holligan 0 likes 80 plays 0  

MCQMC 2022 announcement by Alex Keller

MCQMC 2022 announcement by Alex Keller

From  Liam Holligan 0 likes 70 plays 0  

Yves Atchade, Boston University Approximate spectral gap for MCMC mixing times in high-dimensions (MCQMC 2020)

Yves Atchade, Boston University Approximate spectral gap for MCMC mixing times in high-dimensions

From  Liam Holligan 0 likes 86 plays 0  

David Pfau, Google Deepmind Quantum Monte Carlo and Solving the Many-Electron Schroedinger Equation with Deep Neural Networks (MCQMC 2020)

David Pfau, Google Deepmind Quantum Monte Carlo and Solving the Many-Electron Schroedinger Equation with Deep Neural Networks

From  Liam Holligan 0 likes 112 plays 0  

Mark Jerrum, Queen Mary University London A complexity-theoretic perspective on MCMC (MCQMC 2020)

Mark Jerrum, Queen Mary University London A complexity-theoretic perspective on MCMC (MCQMC 2020)

From  Liam Holligan 0 likes 67 plays 0  

Mario Ullrich, JKU Linz - Random vs. optimal information for L_2-approx imation (MCQMC 2020, 11.08.20)

Mario Ullrich, JKU Linz - Random vs. optimal information for L_2-approx imation

From  Liam Holligan 0 likes 111 plays 0  

Jing Dong, Columbia University - Can Algorithms Collaborate? The Replica Exchange Method (MCQMC 2020, 11.08.20)

Jing Dong, Columbia University - Can Algorithms Collaborate? The Replica Exchange Method

From  Liam Holligan 0 likes 273 plays 0  

Welcome by Mile Giles (MCQMC 2020, 11.08.20)

Welcome by Mile Giles

From  Liam Holligan 0 likes 84 plays 0  

Fred Hickernell, Illinois Institute of Technology Quasi-Monte Carlo Software (MCQMC 2020, 10.08.20)

Fred Hickernell, Illinois Institute of Technology Quasi-Monte Carlo Software (MCQMC 2020, 10.08.20)

From  Liam Holligan 0 likes 257 plays 0  

Aretha Teckentrup, University of Edinburgh - Markov chain Monte Carlo methods (MCQMC 2020, 10.08.20)

Aretha Teckentrup, University of Edinburgh - Markov chain Monte Carlo methods (MCQMC 2020, 10.08.20)

From  Liam Holligan 0 likes 250 plays 0