The study of dynamic biological phenomena, such as differentiation, immune responses, and cancer—which involve multiple, simultaneously occurring biological processes—using destructively measured ...

Biterm Topic Model (BTM) is a word co-occurrence based topic model that learns topics by modeling word-word co-occurrences patterns (e.g., biterms). (In constrast, LDA and PLSA are word-document ...

Recent advances in few-shot learning have demonstrated the potential of prompt-based techniques with pre-trained models, eliminating the need for extensive fine-tuning. However, challenges such as ...

🔍 Automatically identifying and analyzing events from social media platforms (Twitter, Facebook, etc.) 🌎 Covering diverse event types from natural disasters to viral phenomena 🤖 Leveraging AI to ...

The Mexico Institute seeks to improve understanding, communication, and cooperation between Mexico and the United States by promoting original research, encouraging public discussion, and proposing ...

1 Department of Computer Science and Engineering, University of Development Alternative, Dhaka, Bangladesh. 2 Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, ...

With the acceleration of urban and rural power grid construction and the increasing demand for residential electricity, the voltage level of power transmission and transformation equipment has been ...

Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing ...

Some machine learning models belong to either the “generative” or “discriminative” model categories. Yet what is the difference between these two categories of models? What does it mean for a model to ...