publications

2026

1. 

   To Augment or Not to Augment? Diagnosing Distributional Symmetry Breaking

   Hannah Lawrence^*, Elyssa Hofgard^*, Vasco Portilheiro, and 3 more authors

   In International Conference on Learning Representations, 2026

   arXiv Bib HTML

   @inproceedings{lawrence2025augment,
     title = {To Augment or Not to Augment? Diagnosing Distributional Symmetry Breaking},
     author = {Lawrence, Hannah and Hofgard, Elyssa and Portilheiro, Vasco and Chen, Yuxuan and Smidt, Tess and Walters, Robin},
     year = {2026},
     booktitle = {International Conference on Learning Representations},
   }

2025

1. 

   Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

   Xuan Zhang and others

   Foundations and Trends in Machine Learning, 2025

   Bib HTML

   @article{zhang2025artificial,
     title = {Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems},
     author = {Zhang, Xuan and others},
     journal = {Foundations and Trends in Machine Learning},
     volume = {18},
     number = {4},
     pages = {385--912},
     year = {2025},
   }

2024

1. 

   Relaxed Equivariant Graph Neural Networks

   Elyssa Hofgard, Rui Wang, Robin Walters, and 1 more author

   In ICML 2024 Workshop on Geometry-grounded Representation Learning and Generative Modeling, 2024

   arXiv Bib

   @inproceedings{hofgard2024relaxed,
     title = {Relaxed Equivariant Graph Neural Networks},
     author = {Hofgard, Elyssa and Wang, Rui and Walters, Robin and Smidt, Tess},
     booktitle = {ICML 2024 Workshop on Geometry-grounded Representation Learning and Generative Modeling},
     year = {2024},
   }

2. 

   Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution

   Rui Wang, Elyssa Hofgard, Han Gao, and 2 more authors

   In Forty-First International Conference on Machine Learning, 2024

   Bib HTML

   @inproceedings{wang2024discovering,
     title = {Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution},
     author = {Wang, Rui and Hofgard, Elyssa and Gao, Han and Walters, Robin and Smidt, Tess},
     booktitle = {Forty-First International Conference on Machine Learning},
     year = {2024},
   }

2023

1. 

   Potentiality of Automatic Parameter Tuning Suite Available in ACTS Track Reconstruction Software Framework

   Rocky Garg and others

   In 26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023), 2023

   DOI Bib HTML

   @inproceedings{garg2023potentiality,
     title = {Potentiality of Automatic Parameter Tuning Suite Available in {ACTS} Track Reconstruction Software Framework},
     author = {Garg, Rocky and others},
     booktitle = {26th International Conference on Computing in High Energy and Nuclear Physics ({CHEP} 2023)},
     year = {2023},
     doi = {10.1051/epjconf/202429503031},
   }

2. A Rarefaction Approach for Measuring Population Differences in Rare and Common Variation

   Daniel J. Cotter, Elyssa Hofgard, John Novembre, and 2 more authors

   Genetics, 2023

   DOI Bib HTML

   @article{cotter2023rarefaction,
     title = {A Rarefaction Approach for Measuring Population Differences in Rare and Common Variation},
     author = {Cotter, Daniel J. and Hofgard, Elyssa and Novembre, John and Szpiech, Zachary A. and Rosenberg, Noah A.},
     journal = {Genetics},
     volume = {224},
     number = {2},
     year = {2023},
     doi = {10.1093/genetics/iyad070},
   }

3. 

   Search for Dark Photons from Higgs Boson Decays via ZH Production with a Photon Plus Missing Transverse Momentum Signature from pp Collisions at \sqrts = 13\,\textTeV with the ATLAS Detector

   ATLAS Collaboration

   Journal of High Energy Physics, 2023

   DOI Bib HTML

   @article{atlas2023darkphotons,
     title = {Search for Dark Photons from {Higgs} Boson Decays via {ZH} Production with a Photon Plus Missing Transverse Momentum Signature from $pp$ Collisions at $\sqrt{s} = 13\,\text{TeV}$ with the {ATLAS} Detector},
     author = {{ATLAS Collaboration}},
     journal = {Journal of High Energy Physics},
     year = {2023},
     doi = {10.1007/jhep07(2023)133},
   }