Federated learning (FL) has emerged as a promising paradigm for training machine learning models on decentralized data sources without directly exchanging the raw data. However, the application of FL to graph analytics, particularly when dealing with sensitive graph data, presents significant challenges due to the inhe...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Federated learning (FL) offers a promising approach to training machine learning models on decentralized data sources without direct data sharing. However, traditional FL models often operate under the assumption of homogeneous data distributions, which frequently doesn't hold true in real-world scenarios. This researc...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Federated learning (FL) offers a promising approach to training machine learning models on decentralized data sources without directly exchanging data. However, a key challenge in the widespread adoption of FL is the incentive problem: motivating participants to contribute their valuable data and computational resource...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Federated Learning (FL) offers a promising approach to training machine learning models on decentralized data sources without direct data sharing. However, the inherent lack of transparency in FL raises concerns about trust, fairness, and model reliability. This paper explores the critical need for explainable AI (XAI)...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
This paper presents a novel theoretical framework for understanding and modeling temporal dynamics, focusing on the propagation of patterns and information across spatial and temporal scales. The core of the work centers on the development of a model incorporating non-linear interactions and diffusion processes, utiliz...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
This paper proposes a novel approach to multi-scale spatial reasoning by leveraging cellular automata (CA) systems. The core idea is to simulate systems with local interactions, effectively mimicking processes that occur across multiple spatial scales. We introduce a framework where different CA rules are designed to r...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
This research investigates the emergence of complex patterns within stochastic diffusion processes, proposing a novel approach centered on identifying and quantifying 'emergent complexity' through the application of a "statistical resonance" algorithm. We explore how this algorithm maps information flow across a networ...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
This paper explores the extension of standard diffusion equations to incorporate a landscape parameter, introducing a feedback loop that drives the evolution of diffusion patterns. Traditional diffusion models, while widely used, often lack the capacity to generate complex and unpredictable behavior. We propose a novel...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Information diffusion is a fundamental process in many social, biological, and technological systems. Understanding and predicting its spread is crucial for various applications, including network analysis, epidemic spread, and social media influence. Traditional approaches to modeling information diffusion often rely...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Information diffusion is a fundamental process in many social, biological, and technological systems. Understanding and predicting its spread is crucial for various applications, including network analysis, epidemic spread, and social media influence. Traditional approaches to modeling information diffusion often rely...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
This paper explores a novel Bayesian hierarchical diffusion process within vector spaces, designed to facilitate the continuous and adaptive creation of complex mathematical functions. Traditional diffusion methods frequently rely on discrete steps, limiting the generation of intricate and nuanced mathematical expressi...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Non-Euclidean geometries, characterized by non-regular shapes and complex topology, present a unique challenge to traditional geometric modeling. This paper explores the development of a novel class of diffusion processes within these spaces, utilizing continuous, non-linear differential geometry as a foundational fram...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
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