Papers

• HPG-Diff: Hierarchical physics-guided diffusion with differentiable connectivity constraints for topology optimization (2026)
  Jinbo Yang et al.
  4.39
• Reliable mechanistic operator recovery with biologically-informed neural networks: principles for architecture and optimisation design (2026)
  Rebecca M. Crossley et al.
  4.39
• Automatic Differentiation from Scratch: How PyTorch Computes Gradients in Physics-Informed Neural Networks (2026)
  Abdeladhim Tahimi
  4.39
• Topology-Agnostic Mesh Reconstruction of Deformable Objects from Sparse Touch (2026)
  Everest Yang
  4.39
• 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
• A Structure-Adaptive Random Feature Method for High-Dimensional Elliptic PDEs (2026)
  Jiale Linghu et al.
  4.39
• Learned Pairwise Deep Dual-Optimal Inequalities for Stabilizing Column Generation (2026)
  Zhengzhong Ricky You et al.
  3.51
• In-span learning: adapting reduced-order models using their own predictions (2026)
  Amirpasha Hedayat et al.
  2.00
• Characterization of the Basin of Convexity for Multi-Snapshot Spike Deconvolution via Variable Projection (2026)
  Meghna Kalra et al.
  2.00
• Operator-Informed Gaussian Processes for Complex Helmholtz Wavefields: From Synthetic Benchmarks to In Vivo Brain Elastography (2026)
  Boyuan Deng et al.
  2.00
• FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers (2026)
  Peiyu Zang 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
• Explicit Iteration Complexity of Exact Data-Driven Inverse Optimization for Integer Linear Programs (2026)
  Akira Kitaoka
  2.00
• Neptuna: A Comprehensive Machine Learning Framework for Benchmarking Complex Multiphase Flows (2026)
  Harish Ramachandran et al.
  2.00
• Complexity Bounds and Approaches to Learning Projected Gradient Descent Solver Iterates (2026)
  Anjian Li et al.
  2.00
• Geometry-Conditioned Fourier Neural Operators for Cubic Nonlinear Schrodinger Dynamics on Periodic Domains (2026)
  Emmanuel E. Oguadimma et al.
  1.94
• Scalable Gaussian process inference via neural feature maps (2026)
  Anthony Stephenson
  1.89
• Approximation and learning of anisotropic and mixed smooth functions by deep ReLU neural networks (2026)
  Yunfei Yang et al.
  1.89
• Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation (2025)
  Eduardo Fernandes Montesuma et al.
  1.50