Prasun Chaudhuri speaks to expert Subrata Das about the opportunities. Das is currently an adjunct faculty member at ...

The efficient clustering of attributed graphs is a critical and challenging problem that has attracted much attentions across various research fields. Despite recent advancements, many challenges ...

Objective We aimed to estimate prevalence and identify determinants of hypertension in adults aged 15–49 years in Tanzania. Design We analysed cross-sectional survey data from the 2022 Tanzania ...

A Xinfra topic has epochs (which captures the topic change history), allowing it to have an epoch in a Kafka cluster and another in a Northguard cluster, as seen below in figure 13. Figure 13.

Dubbed Adaptive Branching Monte Carlo Tree Search (AB-MCTS), it is a new inference-time scaling algorithm by Sakana AI.

We rarely think about how liquids flow—why honey is thick, water is thin or how molten plastic moves through machines. But ...

A new algorithm opens the door for using artificial intelligence and machine learning to study the interactions that happen ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

This useful study presents a biologically realistic, large-scale cortical model of the rat's non-barrel somatosensory cortex, investigating synaptic plasticity of excitatory connections under varying ...

Functional clustering is a computational technique that groups samples, for instance proteins, into clusters with similar functions. Clustering is the first step in forming a network of functions ...

OTI Lumionics' paper reveals a method for optimizing qubit coupled cluster ansatz on classical computers, advancing quantum simulations for materials discovery.