The new research, published in the Journal of Machine Learning Research, takes an innovative “axiomatic approach” to defining ...

High-entropy alloys (HEAs) offer tunable compositions and surface structures, presenting significant potential for creating novel active sites to enhance CO2 reduction (CO2RR) catalysis, a key process ...

Unlike existing out-of-core GNN frameworks, Capsule eliminates the I/O overhead between the CPU and GPU during the backpropagation process by using graph partitioning and ... It also provides a ...

We develop a novel theoretical framework to prove the safety of an arbitrary-sized MAS with a single GCBF. We propose a new training framework GCBF+ that uses graph neural networks to parameterize a ...

Bell's theorem, the well-known theoretical framework introduced by John Bell decades ago, delineates the limits of classical physical processes arising from relativistic causality principles.

By representing reasoning as a directed acyclic graph (DAG), DoT captures the nuances ... developing next-generation reasoning-specialised models. The framework’s innovative design and theoretical ...

Therefore, we will ask an LLM to create the knowledge graph. Of course, it’s the LMI framework that efficiently guides the LLM to perform this task. We have used LlamaIndex for our project.

Now, researchers have developed a novel theoretical framework that treats DA as a stability problem to explain this parameter. This framework can contribute significantly to turbulence research ...

This framework utilizes a sparse attention mechanism based ... and scalable graph transformers with complexity linear to the size of the graph while also providing theoretical properties of the ...