IEEE

Solving Audio Inverse Problems with a Diffusion Model

Abstract: This paper presents CQT-Diff, a data-driven generative audio model that can, once trained, be used for solving various different audio inverse problems in a problem-agnostic setting.
GitHub

pyforce: Python Framework data-driven model Order Reduction for multi-physiCs problEms

pyforce is a Python package implementing Data-Driven Reduced Order Modelling (DDROM) techniques for applications to multi-physics problems, mainly set in the Nuclear Engineering world. These ...
IEEE

Meta-Learning Inspired Single-Step Generative Model for Expensive Multitask Optimization Problems

Abstract: In expensive multitask optimization problems (ExMTOPs), multiple complex tasks must be optimized simultaneously under limited computational budgets. Existing approaches, often based on ...
thecooldown

Researchers sound alarm over troubling factor predicted to cost global supply chain $540 billion: '[It] has become an accepted cost of doing business'

The magnitude of global food waste is staggering. A new report indicated that food waste is costing retailers and suppliers over half a trillion dollars annually. Avery Dennison's report, "Making the ...
Wired

AI Models Are Starting to Learn by Asking Themselves Questions

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...