4 papers
Forest-Guided Semantic Transport for Label-Supervised Manifold Alignment
Adrien Aumon, Myriam Lizotte, Guy Wolf +2
Label-supervised manifold alignment bridges the gap between unsupervised and correspondence-based paradigms by leveraging shared label information to align multimodal datasets. Sti…
Freeze, Diffuse, Decode: Task-Aware Adaptation of Transformer Embeddings for Antimicrobial Peptide Design
Pankhil Gawade, Adam Izdebski, Myriam Lizotte +4
Pretrained transformers provide rich, general-purpose embeddings, which are transferred to downstream tasks. However, current transfer strategies: fine-tuning and probing, either d…
Random Forest Autoencoders for Guided Representation Learning
Adrien Aumon, Shuang Ni, Myriam Lizotte +3
Extensive research has produced robust methods for unsupervised data visualization. Yet supervised visualization$\unicode{x2013}$where expert labels guide representations$\unicode{…
Manifold Alignment with Label Information
Andres F. Duque, Myriam Lizotte, Guy Wolf +1
Multi-domain data is becoming increasingly common and presents both challenges and opportunities in the data science community. The integration of distinct data-views can be used f…