Machine learning workflow enables faster, more reliable organic crystal structure prediction

Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...
IEEE

Graph Contrastive Learning for Fusion of Graph Structure and Attribute Information

Abstract: Graph Contrastive Learning (GCL) plays a crucial role in multimedia applications due to its effectiveness in analyzing graph-structured data. Existing GCL methods focus on maximizing the ...
GitHub

Machnata — Universal JSON Schema → Protobuf Generator → Portable Data Structures for All Major Languages

In short, this generator helps teams transform standard JSON Schemas into maintainable, language-agnostic data models, enabling consistent integration from embedded devices to cloud systems. This ...
Scientific Research Publishing

Hartmanis, J. and Hemachandra, L.A. (1987) One-Way Functions, Robustness, and the Non-Isomorphism of NP-Complete Sets. Proceeding Structure in Complexity Theory, Ithaca, 16-19 ...

ABSTRACT: A binary complete decision table with many-valued decisions is a table with n attributes and 2 n pairwise distinct rows filled with numbers from the set { 0,1 } . Each row of this table is ...
THE WEEK

Supersized: The no-limit AI data center build-out

Tech firms are investing billions to build massive AI data centers across the U.S. From our morning news briefing to a weekly Good News Newsletter, get the best of The Week delivered directly to your ...
IEEE

AGSEI: Adaptive Graph Structure Estimation With Long-Tail Distributed Implicit Graphs

Abstract: Empowered by their remarkable advantages, graph neural networks (GNN) serve as potent tools for embedding graph-structured data and finding applications across various domains. Particularly, ...