GitHub

pyforeca: Forecastable Component Analysis (ForeCA) in Python

Unlike PCA (maximum variance) or ICA (maximum independence), ForeCA finds components that are maximally forecastable. This makes it ideal for time series analysis where prediction is often the primary ...
Journal of Accountancy

AI tools for finance professionals to prepare and visualize data

AI tools are frequently used in data visualization — this article describes how they can make data preparation more efficient ...
IEEE

Fast Global Sparse Principal Component Analysis for Sensor Reduction in Virtual Metrology

Abstract: In semiconductor manufacturing, virtual metrology (VM) leverages high-dimensional sensor data for real-time quality estimation. However, excessive sensor deployment leads to increased ...
Communications of the ACM

A Decade of Docker Containers

Container instances. Calling docker run on an OCI image results in the allocation of system resources to create a ...
GitHub

TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently ...

🌟 TensorRT LLM is experimenting with Image&Video Generation models in TensorRT-LLM/feat/visual_gen branch. This branch is a prototype and not stable for production ...
IEEE

Double Nonconvex Tensor Robust Kernel Principal Component Analysis and Its Visual Applications

Abstract: Tensor robust principal component analysis (TRPCA), as a popular linear low-rank method, has been widely applied to various visual tasks. The mathematical process of the low-rank prior is ...