Abstract: Power companies employ comprehensive evaluations to manage facilities, such as transformers, lines, and generators, assessing their status and calculating the probability of failure. Within ...

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

We’ve celebrated an extraordinary breakthrough while largely postponing the harder question of whether the architecture we’re scaling can sustain the use cases promised.

A research team has developed a new hybrid artificial intelligence framework that can accurately estimate leaf nitrogen ...

Nvidia is leaning on the hybrid Mamba-Transformer mixture-of-experts architecture its been tapping for models for its new Nemotron 3 models.

Abstract: Change detection (CD) signifies a pivotal domain within remote sensing image processing. The transformer has been introduced in the field of CD for its global perception capabilities.

Transformers are a neural network (NN) architecture, or model, that excels at processing sequential data by weighing the importance of different parts of the input sequence. This allows them to ...

Vision Transformers (ViTs) have become a universal backbone for both image recognition and image generation. Yet their Multi–Head Self–Attention (MHSA) layer still performs a quadratic query–key ...

College of Engineering, Cornell University, Ithaca, New York 14853, United States Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14853, ...

Accurate short-to-subseasonal streamflow forecasts are becoming crucial for effective water management in an increasingly variable climate. However, streamflow forecast remains challenging over ...