Papers

• Extrapolating the emergence of Hamiltonian chaos with random-feature Hamiltonian neural networks (2026)
  Jaesung Choi
  1.94
• Escaping Mode Collapse in LLM Generation via Geometric Regulation (2026)
  Xin Du et al.
  1.83
• ChaosNetBench: Benchmarking Spatio-Temporal Graph Neural Networks on Chaotic Lattice Dynamics (2026)
  Henok Tenaw Moges et al.
  1.83
• Basic Cycle Ratio: Cost-Effective Ranking of Influential Spreaders from Local and Global Perspectives (2025)
  Wenxin Zheng et al.
  1.39
• Versatile Reservoir Computing for Heterogeneous Complex Networks (2025)
  Yao Du et al.
  1.17
• Parallel Machine Learning for Forecasting the Dynamics of Complex Networks (2021)
  Keshav Srinivasan et al.
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• Backpropagation on Dynamical Networks (2022)
  Eugene Tan et al.
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• Enhancing the Inductive Biases of Graph Neural ODE for Modeling Dynamical Systems (2022)
  Suresh Bishnoi et al.
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• Unraveling Low-Dimensional Network Dynamics: A Fusion of Sparse Identification and Proper Orthogonal Decomposition (2023)
  Rui Luo
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• On the weight dynamics of learning networks (2024)
  Nahal Sharafi et al.
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• Master Stability Functions in Complex Networks (2024)
  Suman Acharyya et al.
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