The divergence of ASIC designs makes it difficult to run commonly used modern sequencing analysis pipelines due to software ...

This valuable study introduces a self-supervised machine learning method to classify C. elegans postures and behaviors directly from video data, offering an alternative to the skeleton-based ...

Offered by the Department of Computer Science and Engineering at the Faculty of Science and Technology This course looks at parallel programming models, efficient programming methodologies and ...

The course will provide knowledge in different uses of parallelism in a multi-core computer and especially provide insight into how and when Java can be used to develop parallel programs which can be ...

Abstract: Graph deep learning (GDL) has demonstrated impressive performance in predicting population-based brain disorders (BDs) through the integration of both imaging and non-imaging data. However, ...

Java is not the first language most programmers think of when they start projects involving artificial intelligence (AI) and machine learning ... that can speed up the parallel executions for ...

Moreover, the existing graph representation learning methods mostly rely on graph neural networks (GNNs), which cannot adequately take the dynamic correlations between nodes into consideration, ...

Welcome to the Leo programming language. Leo provides a high-level language that abstracts low-level cryptographic concepts and makes it easy to integrate private applications into your stack. Leo ...

Offered by the Department of Computer Science and Engineering at the Faculty of Science and Technology The course introduces the principles and practice of parallel programming in a functional ...

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained ...