4 citations · 9 across the 7 of their papers we have counts for
8 papers
BarcodeMAE+: Rethinking Masked Pretraining and Global Representations for DNA Barcode Foundation Models
Monireh Safari, Pablo Millan Arias, Scott C. Lowe +3
Many DNA foundation models are pretrained by masking parts of a sequence and asking the model to reconstruct them. Standard masked pretraining exposes the encoder to special [MASK]…
BarcodeMamba+: Advancing State-Space Models for Fungal Biodiversity Research
Tiancheng Gao, Scott C. Lowe, Brendan Furneaux +2
Accurate taxonomic classification from DNA barcodes is a cornerstone of global biodiversity monitoring, yet fungi present extreme challenges due to sparse labelling and long-tailed…
Hyperbolic Multimodal Representation Learning for Biological Taxonomies
ZeMing Gong, Chuanqi Tang, Xiaoliang Huo +6
Taxonomic classification in biodiversity research involves organizing biological specimens into structured hierarchies based on evidence, which can come from multiple modalities su…
Enhancing DNA Foundation Models to Address Masking Inefficiencies
Monireh Safari, Pablo Millan Arias, Scott C. Lowe +3
Masked language modelling (MLM) as a pretraining objective has been widely adopted in genomic sequence modelling. While pretrained models can successfully serve as encoders for var…
Agglomerative Token Clustering
Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor +1
We present Agglomerative Token Clustering (ATC), a novel token merging method that consistently outperforms previous token merging and pruning methods across image classification,…
An Empirical Study into Clustering of Unseen Datasets with Self-Supervised Encoders
Scott C. Lowe, Joakim Bruslund Haurum, Sageev Oore +2
Can pretrained models generalize to new datasets without any retraining? We deploy pretrained image models on datasets they were not trained for, and investigate whether their embe…
CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at Scale
ZeMing Gong, Austin T. Wang, Xiaoliang Huo +4
Measuring biodiversity is crucial for understanding ecosystem health. While prior works have developed machine learning models for taxonomic classification of photographic images a…
BarcodeBERT: Transformers for Biodiversity Analysis
Pablo Millan Arias, Niousha Sadjadi, Monireh Safari +9
In the global challenge of understanding and characterizing biodiversity, short species-specific genomic sequences known as DNA barcodes play a critical role, enabling fine-grained…