The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

Assessing the progress of new AI language models can be as challenging as training them. Stanford researchers offer a new approach.

A Weighted Zero-inflated Sensitive LSTM model (WZS-LSTM) which integrates both a stacked LSTM architecture and a Weighted Zero-inflated Sensitive (WZS) loss function was proposed to improve LSTM’s ...

Learn how Kimi K2’s open-weight framework and sparse architecture are transforming AI coding and fostering global ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

The normal leakage flux induces strong eddy currents on the surface of nanocrystalline core, producing significant leakage flux eddy current loss (LFECL). Since LFECL is proportional to the square of ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

Hi, thank you for the great work and open-sourcing the code. I'm currently training the inversion model using a single H100 GPU, and I wanted to check if the training behavior I'm seeing is expected.

If you like our Framework, don't hesitate to ⭐ star this repository ⭐. This helps us to make the Framework more better and scalable to different models and methods 🤗. A modular and efficient ...

Liver cancer is the sixth most common cancer globally and a leading cause of cancer-related deaths. Accurate segmentation of liver tumors is a crucial step for the management of the disease, but ...