A team of researchers at the University of California, Los Angeles (UCLA) has introduced a novel framework for designing and ...

Further investigation on betweenness centrality reveals that the accuracy of deep learning is not as good as some tailor-made, tuned approximation algorithms. However, deep learning offers a nice ...

In this paper, we develop a deep learning network to make personalized predictions ... user's features and his historical event lists by sequence-to-sequence (Seq2Seq) structure and make predictions ...

Recent advancements in deep learning, particularly large language ... with predicting proteins’ biological properties (e.g., 3D structures, functions) based on their AA residue sequences.

Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, ChangChun 130012, China ...

One of the major threats facing the nascent AI world is hallucinations by chatbots. Google DeepMind's AlphaEvolve has the versatility of LLMs -- to summarise documents, generate code, and generate new ...

The extracted features contain few irrelevant information; therefore, we proposed an improved Quantum Theory-based Marine Predator Optimization algorithm ... encoder network. The newly generated ...

AlphaTensor, from 2022, used the reinforcement learning method to produce novel algorithms. Fun Search, from 2024, used an evolutionary method to generate more efficient code for a given problem.

Google Deepmind has unveiled AlphaEvolve, a system that uses large language models to automate the discovery and refinement of algorithms. The aim is to develop new algorithms, systematically improve ...