Obtaining genetics insights from deep learning via explainable artificial intelligence
Artificial intelligence (AI) models based on deep learning now represent the state of the art
for making functional predictions in genomics research. However, the underlying basis on …
for making functional predictions in genomics research. However, the underlying basis on …
Survey of explainable AI techniques in healthcare
Artificial intelligence (AI) with deep learning models has been widely applied in numerous
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …
Explainability for large language models: A survey
Large language models (LLMs) have demonstrated impressive capabilities in natural
language processing. However, their internal mechanisms are still unclear and this lack of …
language processing. However, their internal mechanisms are still unclear and this lack of …
Transformers in single-cell omics: a review and new perspectives
Recent efforts to construct reference maps of cellular phenotypes have expanded the
volume and diversity of single-cell omics data, providing an unprecedented resource for …
volume and diversity of single-cell omics data, providing an unprecedented resource for …
From anecdotal evidence to quantitative evaluation methods: A systematic review on evaluating explainable ai
The rising popularity of explainable artificial intelligence (XAI) to understand high-performing
black boxes raised the question of how to evaluate explanations of machine learning (ML) …
black boxes raised the question of how to evaluate explanations of machine learning (ML) …
A survey on automated fact-checking
Fact-checking has become increasingly important due to the speed with which both
information and misinformation can spread in the modern media ecosystem. Therefore …
information and misinformation can spread in the modern media ecosystem. Therefore …
A review on the attention mechanism of deep learning
Attention has arguably become one of the most important concepts in the deep learning
field. It is inspired by the biological systems of humans that tend to focus on the distinctive …
field. It is inspired by the biological systems of humans that tend to focus on the distinctive …
Merlot: Multimodal neural script knowledge models
As humans, we understand events in the visual world contextually, performing multimodal
reasoning across time to make inferences about the past, present, and future. We introduce …
reasoning across time to make inferences about the past, present, and future. We introduce …
A survey on vision transformer
Transformer, first applied to the field of natural language processing, is a type of deep neural
network mainly based on the self-attention mechanism. Thanks to its strong representation …
network mainly based on the self-attention mechanism. Thanks to its strong representation …
Interpretable and generalizable graph learning via stochastic attention mechanism
Interpretable graph learning is in need as many scientific applications depend on learning
models to collect insights from graph-structured data. Previous works mostly focused on …
models to collect insights from graph-structured data. Previous works mostly focused on …