As the RISC-V ecosystem grows, startups struggle to verify complex chips before tape-out. Chennai-based startup addresses ...

The current AI regression testing systems consider the new code changes, past failures, and dependency indicators to decide which test cases are the most important to a particular release. Areas with ...

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), ...

The development of this repository was inspired by the paper "AdaWorld: Learning Adaptable World Models with Latent Actions". To read the entire paper, visit https ...

The data science landscape is not merely evolving; it is undergoing a profound transformation. The graduate of 2021, equipped ...

Google’s Scenario Planner gives you a no-code way to turn Marketing Mix Model insights into budget and ROI decisions. The ...

This repository is an example accompanying the DES RAP Book — an open educational resource on reproducible discrete-event simulation (DES) in Python and R. The book demonstrates best practices for ...

Its use results in faster development, cleaner testbenches, and a modern software-oriented approach to validating FPGA and ...

Abstract: Advancements in large multimodal models (LMMs) for text and image understanding have provided a new paradigm for semiconductor intelligent manufacturing. However, due to the ...

Background: In patients with acute coronary syndrome (ACS), marital status may have a significant impact on the prognosis. However, it remains unclear whether marital status influences in-hospital ...

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...

Abstract: Deep learning approaches have gained significant traction in holographic imaging, with diffusion models—an emerging class of deep generative models—showing particular promise in hologram ...