Abstract: Many graph-based algorithms in high performance computing (HPC) use approximate solutions due to having algorithms that are computationally expensive or serial in nature. Neural acceleration ...

Abstract: Robust matrix completion refers to recovering a low-rank matrix given a subset of the entries corrupted by gross errors, and has various applications since many real-world signals can be ...

Struct2GO is a protein function prediction model based on self-attention graph pooling, which utilizes structural information from AlphaFold2 to augment the accuracy and generality of the model's ...

Recently, a research team from the Rudolf Technology Center in Slovenia proposed a new method to optimize the sparse subgraph problem, which has wide applications in fields such as network analysis ...

A growing number of AI processors are being designed around specific workloads rather than standardized benchmarks, ...

Context Aware RAG is a flexible library designed to seamlessly integrate into existing data processing workflows to build customized data ingestion and retrieval (RAG) pipelines. With Context Aware ...

By institutionalising muhūrta s within mathematics, the UGC is effectively telling students that astrological determinism is ...

What about ChatGPT and related large AI Systems? How will they impact us all? As a longtime researcher in AI, I'm excited about the ways in which these new AI systems can improve our healthcare, ...