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Hannah Bull

3 accepted papers

2026

TriForces: Augmenting Atomistic GNNs for Transferable Representations

ICML 2026poster

Machine learning interatomic potentials (MLIPs) achieve excellent accuracy when trained on large Density Functional Theory (DFT) data. To be useful in practice, they must often be adapted to target chemistries using small and expensive task-specific datasets. However, MLIPs transfer inconsistently a…

Cited by 0SourceScholar
2022

Automatic Dense Annotation of Large-Vocabulary Sign Language Videos

ECCV 2022poster

"Recently, sign language researchers have turned to sign language interpreted TV broadcasts, comprising (i) a video of continuous signing and (ii) subtitles corresponding to the audio content, as a readily available and large-scale source of training data. One key challenge in the usability of such…

Cited by 24SourcePDFScholar
2021

Aligning Subtitles in Sign Language Videos

ICCV 2021poster

The goal of this work is to temporally align asynchronous subtitles in sign language videos. In particular, we focus on sign-language interpreted TV broadcast data comprising (i) a video of continuous signing, and (ii) subtitles corresponding to the audio content. Previous work exploiting such weakl…

Cited by 39PDFScholar