In the context of global energy shortages, traditional energy sources face issues of limited reserves and high prices. As a result, the importance of energy storage technology is increasingly ...

Antibiotic resistance is emerging as a critical global public health threat. The precise prediction of bacterial antibiotic resistance genes (ARGs) and phenotypes is essential to understand resistance ...

This project enables the generation of novel, valid, and drug-like molecules as SMILES strings, using a two-stage approach: Stage 1: Train an LSTM model on a large SMILES dataset for next-token ...

Sequence labeling models are quite popular in many NLP tasks, such as Named Entity Recognition (NER), part-of-speech (POS) tagging and word segmentation. State-of-the-art sequence labeling models ...

Abstract: Long Short-Term Memory (LSTM) networks are particularly useful in recommender systems since user preferences change over time. Unlike traditional recommender models which assume static ...

ABSTRACT: The application of artificial intelligence in stock price forecasting is an important area of research at the intersection of finance and computer science, with machine learning techniques ...

ABSTRACT: Accurate precipitation forecasting is crucial for mitigating the impacts of extreme weather events and enhancing disaster preparedness. This study evaluates the performance of Long ...