Latest Research in Physics Informed Neural Learning

Top Research Topics in Physics Informed Neural Learning

• Machine Learning — 62 papers
• Numerical Analysis — 45 papers
• Model Reduction and Neural Networks — 29 papers
• Statistical Mechanics — 18 papers
• Dynamical Systems — 11 papers
• Machine Learning — 10 papers
• Nonlinear Dynamics and Pattern Formation — 9 papers
• Neural dynamics and brain function — 8 papers
• Chaotic Dynamics — 7 papers
• Adaptation and Self-Organizing Systems — 7 papers

Highest-Cited Papers

1. Hyperedge overlap regulates stochastic resonance in higher-order networks
2. From Proportional Rectangles to Sampled Analog Root Computation
3. A novel new iterative method–physics-informed neural networks approach for accurate and efficient solutions of nonlinear damped Burgers’ equations
4. Stabilizing PDE–ML coupled systems
5. MERLIN SCIENCE — Phi-Scaled Vector Quantization of Neural Phase-Coherence — E8 Intelligence Research
6. Path Memory and Multistability in Coupled Oscillator Networks: A Numerical Study
7. Path Memory and Multistability in Coupled Oscillator Networks: A Numerical Study
8. MERLIN SCIENCE — Phi-Scaled Vector Quantization of Neural Phase-Coherence — E8 Intelligence Research
9. Hard-constrained Physics-informed Neural Networks for Interface Problems
10. Neural network-assisted refinement of traditional schemes for one-dimensional scalar conservation laws
11. Morphological Memory: Grounding Synthetic Agent Architectures in Basal Cognition and Non-Neural Morphogenesis
12. Topological Memory and Hysteresis in Reconfigurable Dusty Plasma Networks
13. Interpolatory dynamical low-rank approximation: theoretical foundations and algorithms
14. Physical knowledge on historical data matters more than enforcing physical constraints on the forecast
15. Amortizing Physics-Informed Neural Solvers via Graph Hypernetworks
16. Extended dynamic mode decomposition with Fourier dictionaries: Error bounds and fast implementation
17. Martingale theory for heat and phase-space contraction in heterogeneous diffusions
18. SIPHy: Sparse identification of port-Hamiltonian systems from noisy data
19. Approximation Theorems for High-Dimensional Canonical U-Statistics: Gaussian Chaos and Phase Transition
20. Target Search Optimization by Threshold Resetting (4 citations)

Sub-Regions

• Statistical Mechanics — 77 papers
• Numerical Analysis — 63 papers
• Model Reduction and Neural Networks — 57 papers
• Machine Learning — 38 papers
• Chaotic Dynamics — 24 papers
• Adaptation and Self-Organizing Systems — 18 papers