Timezone: »
Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows
Pim de Haan · Roberto Bondesan
We propose a continuous normalizing flow for sampling from the high-dimensional probability distributions of Quantum Field Theories in Physics. In contrast to the deep architectures used so far for this task, our proposal is based on a shallow design and incorporates the symmetries of the problem. We test our model on the ϕ⁴ theory, showing that it systematically outperforms a realNVP baseline in sampling efficiency, with the difference between the two increasing for larger lattices. On the largest lattice we consider, of size 32 x 32, we improve a key metric, the effective sample size, from 1% to 66% w.r.t. the realNVP baseline.
Author Information
Pim de Haan (Qualcomm AI Research, University of Amsterdam)
Roberto Bondesan (Qualcomm AI Research)
More from the Same Authors
-
2022 : Robust Scheduling with GFlowNets »
David Zhang · Corrado Rainone · Markus Peschl · Roberto Bondesan -
2022 : Deconfounded Imitation Learning »
Risto Vuorio · Pim de Haan · Johann Brehmer · Hanno Ackermann · Daniel Dijkman · Taco Cohen -
2023 : FoMo rewards: Casting foundation models as generic reward functions »
Ekdeep S Lubana · Pim de Haan · Taco Cohen · Johann Brehmer -
2023 : FoMo rewards: Casting foundation models as generic reward functions »
Ekdeep S Lubana · Pim de Haan · Taco Cohen · Johann Brehmer -
2023 : Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers »
Pim de Haan · Taco Cohen · Johann Brehmer -
2023 : Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers »
Pim de Haan -
2023 Poster: EDGI: Equivariant Diffusion for Planning with Embodied Agents »
Johann Brehmer · Joey Bose · Pim de Haan · Taco Cohen -
2023 Poster: Geometric Algebra Transformer »
Johann Brehmer · Pim de Haan · Sönke Behrends · Taco Cohen -
2022 Poster: Weakly supervised causal representation learning »
Johann Brehmer · Pim de Haan · Phillip Lippe · Taco Cohen -
2020 Poster: Natural Graph Networks »
Pim de Haan · Taco Cohen · Max Welling -
2019 Poster: Causal Confusion in Imitation Learning »
Pim de Haan · Dinesh Jayaraman · Sergey Levine -
2019 Oral: Causal Confusion in Imitation Learning »
Pim de Haan · Dinesh Jayaraman · Sergey Levine -
2018 : Poster Session »
Sujay Sanghavi · Vatsal Shah · Yanyao Shen · Tianchen Zhao · Yuandong Tian · Tomer Galanti · Mufan Li · Gilad Cohen · Daniel Rothchild · Aristide Baratin · Devansh Arpit · Vagelis Papalexakis · Michael Perlmutter · Ashok Vardhan Makkuva · Pim de Haan · Yingyan Lin · Wanmo Kang · Cheolhyoung Lee · Hao Shen · Sho Yaida · Dan Roberts · Nadav Cohen · Philippe Casgrain · Dejiao Zhang · Tengyu Ma · Avinash Ravichandran · Julian Emilio Salazar · Bo Li · Davis Liang · Christopher Wong · Glen Bigan Mbeng · Animesh Garg -
2018 : Coffee Break and Poster Session I »
Pim de Haan · Bin Wang · Dequan Wang · Aadil Hayat · Ibrahim Sobh · Muhammad Asif Rana · Thibault Buhet · Nicholas Rhinehart · Arjun Sharma · Alex Bewley · Michael Kelly · Lionel Blondé · Ozgur S. Oguz · Vaibhav Viswanathan · Jeroen Vanbaar · Konrad Żołna · Negar Rostamzadeh · Rowan McAllister · Sanjay Thakur · Alexandros Kalousis · Chelsea Sidrane · Sujoy Paul · Daphne Chen · Michal Garmulewicz · Henryk Michalewski · Coline Devin · Hongyu Ren · Jiaming Song · Wen Sun · Hanzhang Hu · Wulong Liu · Emilie Wirbel