Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox

Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions


Jul 18, 2022
Ryan Abbott, Michael S. Albergo, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Gurtej Kanwar, S├ębastien Racani├Ęre, Danilo J. Rezende, Fernando Romero-L├│pez, Phiala E. Shanahan, Betsy Tian, Julian M. Urban

* 13 pages, 5 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Flow-based sampling in the lattice Schwinger model at criticality


Feb 23, 2022
Michael S. Albergo, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Gurtej Kanwar, S├ębastien Racani├Ęre, Danilo J. Rezende, Fernando Romero-L├│pez, Phiala E. Shanahan, Julian M. Urban

* 5 pages main text, 3 pages supplementary material. 4 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Simulation Intelligence: Towards a New Generation of Scientific Methods


Dec 06, 2021
Alexander Lavin, Hector Zenil, Brooks Paige, David Krakauer, Justin Gottschlich, Tim Mattson, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, At─▒l─▒m G├╝ne┼č Baydin, Carina Prunkl, Brooks Paige, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob Macke, Kyle Cranmer, Jiaxin Zhang, Haruko Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

A neural simulation-based inference approach for characterizing the Galactic Center $╬│$-ray excess


Oct 13, 2021
Siddharth Mishra-Sharma, Kyle Cranmer

* 20+3 pages, 10+4 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Flow-based sampling for multimodal distributions in lattice field theory


Jul 01, 2021
Daniel C. Hackett, Chung-Chun Hsieh, Michael S. Albergo, Denis Boyda, Jiunn-Wei Chen, Kai-Feng Chen, Kyle Cranmer, Gurtej Kanwar, Phiala E. Shanahan

* 33 pages, 29 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Flow-based sampling for fermionic lattice field theories


Jun 10, 2021
Michael S. Albergo, Gurtej Kanwar, S├ębastien Racani├Ęre, Danilo J. Rezende, Julian M. Urban, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Phiala E. Shanahan

* 26 pages, 5 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Exact and Approximate Hierarchical Clustering Using A*


Apr 14, 2021
Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum

* 30 pages, 9 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Introduction to Normalizing Flows for Lattice Field Theory


Jan 20, 2021
Michael S. Albergo, Denis Boyda, Daniel C. Hackett, Gurtej Kanwar, Kyle Cranmer, S├ębastien Racani├Ęre, Danilo Jimenez Rezende, Phiala E. Shanahan

* 38 pages, 5 numbered figures, Jupyter notebook included as ancillary file 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Hierarchical clustering in particle physics through reinforcement learning


Nov 16, 2020
Johann Brehmer, Sebastian Macaluso, Duccio Pappadopulo, Kyle Cranmer

* Accepted at the Machine Learning and the Physical Sciences workshop at NeurIPS 2020 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Simulation-based inference methods for particle physics


Nov 02, 2020
Johann Brehmer, Kyle Cranmer

* To appear in "Artificial Intelligence for Particle Physics", World Scientific Publishing Co 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email
1
2
3
4
5
>>