Papers

• Graph-Regularized Low-Rank Matrix Completion by Variable Projection (2026)
  Beno\^it Loucheur et al.
  5.01
• Spectral-Informed Neural Networks Outperform Spectral Methods in High-dimensional PDEs (2026)
  Tianchi Yu et al.
  4.39
• Approximation of solutions of parameter-dependent problems by residual neural networks (2026)
  Ana Carpio
  4.39
• Microstructure-Conditioned Surrogate Models for Graded Multiscale Optimization of Mycelium Composites (2026)
  J. Storm et al.
  4.39
• Multiplicity of Stable Attractors in Disordered Neural Models (2026)
  Raffaele Marino et al.
  3.51
• Operator-Informed Gaussian Processes for Complex Helmholtz Wavefields: From Synthetic Benchmarks to In Vivo Brain Elastography (2026)
  Boyuan Deng et al.
  2.00
• Shallower ReLU Network Representations via Exact Linear Algebra (2026)
  Kilian Rue{\ss} et al.
  2.00
• A Defense of the Quadratic Model (2026)
  Alexandru Meterez et al.
  2.00
• Remedying Coarsening-Based GNN Training under Heterophily via Adaptive Complementary Enhancement (2026)
  Guoming Li et al.
  2.00
• Generalized Neural Operator for Parametric and Boundary-Value Problems (2026)
  Ruoyan Li et al.
  2.00
• Energy Manifold Natural Gradient Descent: Riemannian Optimization for Neural PDE Solvers (2026)
  Zhangyong Liang et al.
  2.00
• Latent PDE mapping for efficient physics-informed learning across geometries with limited data (2026)
  Ingvild Askim Adde et al.
  2.00
• Neptuna: A Comprehensive Machine Learning Framework for Benchmarking Complex Multiphase Flows (2026)
  Harish Ramachandran et al.
  2.00
• Local-Global Geometric Insights for Graph Neural Networks via Entropic Curvature (2026)
  Rachid Caich et al.
  2.00
• Complexity Bounds and Approaches to Learning Projected Gradient Descent Solver Iterates (2026)
  Anjian Li et al.
  2.00
• Beyond Negative-Ridge Endpoints: Mixed-Sign Spectral Regularization via Negative-Shifted Gradient Descent (2026)
  Peng Zhao
  2.00
• Geometry-Conditioned Fourier Neural Operators for Cubic Nonlinear Schrodinger Dynamics on Periodic Domains (2026)
  Emmanuel E. Oguadimma et al.
  1.94
• Approximation and learning of anisotropic and mixed smooth functions by deep ReLU neural networks (2026)
  Yunfei Yang et al.
  1.89
• Statistical physics of deep learning: Optimal learning of a multi-layer perceptron near interpolation (2025)
  Jean Barbier et al.
  1.50
• Statistical mechanics of extensive-width Bayesian neural networks near interpolation (2025)
  Jean Barbier et al.
  1.22
• MIXPINN: Mixed-Material Simulations by Physics-Informed Neural Network (2025)
  Xintian Yuan et al.
  1.11
• Optimal generalisation and learning transition in extensive-width shallow neural networks near interpolation (2025)
  Jean Barbier et al.
  1.00
• Hybridnet: Integrating Model-based And Data-driven Learning To Predict Evolution Of Dynamical Systems (2018)
  Yun Long, Xueyuan She, Saibal Mukhopadhyay
  0.00