Figure 4-14 from COMPUTATIONAL REPRESENTATION OF LINGUISTIC

Figure 4-14: Overview of thesis chapters showing chapters 1-4 completed (grey chevrons). - "COMPUTATIONAL REPRESENTATION OF LINGUISTIC SEMANTICS FOR REQUIREMENT ANALYSIS IN ENGINEERING DESIGN"

Two leading premotives in the 8-tone main theme of Bach's Kunst der

Deep learning for protein complex structure prediction - ScienceDirect

Moving towards accurate and early prediction of language delay with network science and machine learning approaches

Toward a Cenozoic history of atmospheric CO2

Cross-modal and cross-language activation in bilinguals reveals lexical competition even when words or signs are unheard or unseen

The Nucleotide Transformer: Building and Evaluating Robust Foundation Models for Human Genomics

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets, Genome Biology

Sparsity of higher-order landscape interactions enables learning and prediction for microbiomes

Improving molecular representation learning with metric learning-enhanced optimal transport - ScienceDirect

Applied Sciences, Free Full-Text

Advances in knowledge representation by Andgar22 - Issuu

Representation learning for neural population activity with Neural Data Transformers – arXiv Vanity