Quantum walks sound abstract, but they sit at the center of a very concrete race: who will harness quantum mechanics to solve ...

Abstract: Graph cut algorithms are widely used to solve min-cut/max-flow problems across various optimization applications. A common approach in recent FPGA accelerators of graph cut algorithms is to ...

The first thing to understand about the TikTok deal is that it’s not actually a deal—at least not in any official capacity yet. Trump’s executive order Thursday simply delays the Chinese social media ...

import torch @torch.compile(backend="inductor") def fn(src, index, base_tensor): src = src + 10 torch.use_deterministic_algorithms(True) base_tensor.scatter_(0, index ...

This repository contains the source code and datasets for our proposed framework on temporal action segmentation, as described in the paper titled Semantic Smoothness Optimization via Graph-Cut Energy ...

ABSTRACT: To effectively evaluate a system that performs operations on UML class diagrams, it is essential to cover a large variety of different types of diagrams. The coverage of the diagram space ...

Here's how to optimize for LLMs, knowledge graphs, and modern search engines and build a digital footprint recommendation engines trust. SEO is all about optimizing for, well, search. In 2018, I ...

Royalty-free licenses let you pay once to use copyrighted images and video clips in personal and commercial projects on an ongoing basis without requiring additional payments each time you use that ...

Abstract: Graph cut algorithms are popular in optimization tasks related to min-cut and max-flow problems. However, modern FPGA graph cut algorithm accelerators still need performance and memory ...