Zijie's Homepage
My research interest lies in generative AI, AI4Science, machine learning in general, with a special focus on dynamical system modeling, knowledge graph reasoning, LLMs and diffusion …
In this paper, we propose coupled graph ODE: a novel latent ordinary diferential equation (ODE) generative model that learns the coupled dynamics of nodes and edges with a graph neural …
Coupled Graph ODE for Learning Interacting System Dynamics
Aug 14, 2021 · In this paper, we propose coupled graph ODE: a novel latent ordinary differential equation (ODE) generative model that learns the coupled dynamics of nodes and edges with a …
A dynamic knowledge graph approach to distributed self-driving …
Jan 23, 2024 · In this work, we develop an architecture for distributed self-driving laboratories within The World Avatar project, which seeks to create an all-encompassing digital twin based …
Using dynamic knowledge graphs to detect emerging …
Jun 21, 2024 · Knowledge graphs represent relationships between entities. These graphs can take dynamic forms to trace changes along time through text models and further used by …
Generalizing Graph ODE for Learning Complex System Dynamics …
Aug 4, 2023 · Here, we present GG-ODE (Generalized Graph Ordinary Differential Equations), a machine learning framework for learning continuous multi-agent system dynamics across …
4 Chapter 4: Introduction to System Dynamics Modeling
Along the way, you will learn some of the basics of system dynamics model building. For each exercise you will build a running simulator of a simple system. Your model will include …
Learning on knowledge graph dynamics provides an early …
May 17, 2021 · Here we describe DELPHI (Dynamic Early-warning by Learning to Predict High Impact), a framework that provides an early-warning signal for ‘impactful’ research by …
ERD-Net: Modeling entity and relation dynamics for Temporal Knowledge …
Temporal Knowledge Graph (TKG) has garnered significant attention and applications due to its immense potential and impact in event prediction. Existing approaches primarily focus on …
Graph Dynamics: Learning and Representation – MIT Media Lab
Feb 1, 2006 · In graph dynamics, states are graphical structures, corresponding to different hypothesis for representation, and motion is the correction or repair of an antecedent …