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Hybrid hash function locks collision resistance behind two independent math problems

Hybrid hash function post-quantum cryptography research: a new paper on IACR ePrint formalizes a construction whose collision ...
Investopedia

Understanding the Probability Density Function (PDF) in Finance

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...
Investopedia

Discrete Probability Distribution: Overview and Examples

Julie Young is an experienced financial writer and editor. She specializes in financial analysis in capital planning and investment management. Eric's career includes extensive work in both public and ...
IEEE

UniDyG: A Unified and Effective Representation Learning Approach for Large Dynamic Graphs

Abstract: Dynamic graphs, which capture time-evolving edges between nodes, are formulated in continuous-time or discrete-time dynamic graphs. They differ in temporal granularity: Continuous-Time ...
C&EN

Accurate Prediction of NMR Chemical Shifts: Integrating DFT Calculations with Three-Dimensional Graph Neural Networks

Department of Chemistry, New York University, New York, New York 10003, United States Department of Chemistry, New York University, New York, New York 10003, United States Simons Center for ...
GitHub

DiGress: Discrete Denoising diffusion models for graph generation

Update (Nov 20th, 2023): Working with large graphs (more than 100-200 nodes)? Consider using SparseDiff, a sparse version of DiGress: https://github.com/qym7 ...
Frontiers

Efficient graph convolutional networks for seizure prediction using scalp EEG

Epilepsy is a chronic brain disease that causes persistent and severe damage to the physical and mental health of patients. Daily effective prediction of epileptic seizures is crucial for epilepsy ...
IEEE

Graph Convolutional Network Discrete Hashing for Cross-Modal Retrieval

Abstract: With the rapid development of deep neural networks, cross-modal hashing has made great progress. However, the information of different types of data is asymmetrical, that is to say, if the ...
Frontiers

A Graph-Based Framework for Multiscale Modeling of Physiological Transport

Trillions of chemical reactions occur in the human body every second, where the generated products are not only consumed locally but also transported to various locations in a systematic manner to ...
PNAS

The effective graph reveals redundancy, canalization, and control pathways in biochemical regulation and signaling

Many biological networks are modeled with multivariate discrete dynamical systems. Current theory suggests that the network of interactions captures salient features of system dynamics, but it misses ...
Nature

Human brain networks function in connectome-specific harmonic waves

A key characteristic of human brain activity is coherent, spatially distributed oscillations forming behaviour-dependent brain networks. However, a fundamental principle underlying these networks ...