Phiala E. Shanahan

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 16

Top Topics

Sampling Strategies

Theoretical Framework

Boolean Algebra

Top Venues

Publications

Ryan Abbott, Aleksandar Botev, Denis Boyda, Daniel C. Hackett, Gurtej Kanwar, Sébastien Racanière, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Julian M. Urban
Applications of flow models to the generation of correlated lattice QCD ensembles. CoRR (2024)
Ryan Abbott, Michael S. Albergo, Denis Boyda, Daniel C. Hackett, Gurtej Kanwar, Fernando Romero-López, Phiala E. Shanahan, Julian M. Urban
Practical applications of machine-learned flows on gauge fields. CoRR (2024)
Ryan Abbott, Michael S. Albergo, Aleksandar Botev, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Gurtej Kanwar, Alexander G. de G. Matthews, Sébastien Racanière, Ali Razavi, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Julian M. Urban
Normalizing flows for lattice gauge theory in arbitrary space-time dimension. CoRR (2023)
Kyle Cranmer, Gurtej Kanwar, Sébastien Racanière, Danilo J. Rezende, Phiala E. Shanahan
Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics. CoRR (2023)
Ryan Abbott, Michael S. Albergo, Aleksandar Botev, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Alexander G. de G. Matthews, Sébastien Racanière, Ali Razavi, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Julian M. Urban
Aspects of scaling and scalability for flow-based sampling of lattice QCD. CoRR (2022)
Denis Boyda, Salvatore Calì, Sam Foreman, Lena Funcke, Daniel C. Hackett, Yin Lin, Gert Aarts, Andrei Alexandru, Xiao-Yong Jin, Biagio Lucini, Phiala E. Shanahan
Applications of Machine Learning to Lattice Quantum Field Theory. CoRR (2022)
Michael S. Albergo, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Gurtej Kanwar, Sébastien Racanière, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Julian M. Urban
Flow-based sampling in the lattice Schwinger model at criticality. CoRR (2022)
Ryan Abbott, Michael S. Albergo, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Gurtej Kanwar, Sébastien Racanière, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Betsy Tian, Julian M. Urban
Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions. CoRR (2022)
Salvatore Calì, Daniel C. Hackett, Yin Lin, Phiala E. Shanahan, Brian Xiao
Neural-network preconditioners for solving the Dirac equation in lattice gauge theory. CoRR (2022)
Daniel C. Hackett, Chung-Chun Hsieh, Michael S. Albergo, Denis Boyda, Jiunn-Wei Chen, Kai-Feng Chen, Kyle Cranmer, Gurtej Kanwar, Phiala E. Shanahan
Flow-based sampling for multimodal distributions in lattice field theory. CoRR (2021)
Michael S. Albergo, Gurtej Kanwar, Sébastien Racanière, Danilo J. Rezende, Julian M. Urban, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Phiala E. Shanahan
Flow-based sampling for fermionic lattice field theories. CoRR (2021)
Michael S. Albergo, Denis Boyda, Daniel C. Hackett, Gurtej Kanwar, Kyle Cranmer, Sébastien Racanière, Danilo Jimenez Rezende, Phiala E. Shanahan
Introduction to Normalizing Flows for Lattice Field Theory. CoRR (2021)
Denis Boyda, Gurtej Kanwar, Sébastien Racanière, Danilo Jimenez Rezende, Michael S. Albergo, Kyle Cranmer, Daniel C. Hackett, Phiala E. Shanahan
Sampling using SU(N) gauge equivariant flows. CoRR (2020)
Danilo Jimenez Rezende, George Papamakarios, Sébastien Racanière, Michael S. Albergo, Gurtej Kanwar, Phiala E. Shanahan, Kyle Cranmer
Normalizing Flows on Tori and Spheres. CoRR (2020)
Danilo Jimenez Rezende, George Papamakarios, Sébastien Racanière, Michael S. Albergo, Gurtej Kanwar, Phiala E. Shanahan, Kyle Cranmer
Normalizing Flows on Tori and Spheres. ICML (2020)
Gurtej Kanwar, Michael S. Albergo, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Sébastien Racanière, Danilo Jimenez Rezende, Phiala E. Shanahan
Equivariant flow-based sampling for lattice gauge theory. CoRR (2020)