Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

Abstract: This paper presents the design of a framework for loading a pre-trained model in PyTorch on embedded devices to run local inference. Currently, TensorFlow Lite is the most widely used ...

ABSTRACT: This paper explores the application of various time series prediction models to forecast graphical processing unit (GPU) utilization and power draw for machine learning applications using ...

This repository provides a comprehensive benchmark comparison of Variational Autoencoder (VAE) implementations for time series anomaly detection. The benchmark evaluates performance across multiple ...

Cybersecurity researchers have discovered vulnerable code in legacy Python packages that could potentially pave the way for a supply chain compromise on the Python Package Index (PyPI) via a domain ...

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

Evaluates Python SAST, DAST, IAST and LLM-based security tools that power AI development and vibe coding LOS ALTOS, CA, UNITED STATES, November 6, 2025 /EINPresswire ...

Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States ...

The first Linux Docker container fully tested and optimized for NVIDIA RTX 5090 and RTX 5060 Blackwell GPUs, providing native support for both PyTorch and TensorFlow with CUDA 12.8. Run machine ...