Numerical analysis & scientific computing
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- Spectral density estimation for normal matrices
- adapol: Adaptive pole-fitting for quantum many-body physics
- Quantum Frozen--Oseen homotopy analysis method with LCHS for solving nonlinear partial differential equations
- Structure-preserving Fourier Neural Operators for Long-time Cahn-Hilliard Dynamics under Coarse Temporal Supervision
- Mixed updating in structured populations
- Landau–Lifshitz–Gilbert equation written in a suitable form for numerical solution via explicit solvers
- BandPC: Learning Residual-Band Preconditioner Combinations for Flexible Conjugate Gradient Solvers
- The Mode of Null-A: Compositional Computation of a Generalized Inverse
- An energy-based discontinuous Galerkin method for wave equations on complex geometric domains
- An Approximate Method for Modeling Plasmons on Graphene with Time- and Space-dependent Properties
- Catheter-modulated transient solute dispersion in micropolar annular flow with a retentive and absorptive arterial wall
- Solving Linear Systems in Õ(mn log κ/ε) Bit Operations
- Running error bounds in finite element kernels
- Computing Spectral Properties of Differential Operators on Surfaces
- Finite element approximation for the Bessel (p,s)-Laplacian
- The double descent and Runge phenomena in overparametrized polynomial interpolation
- An augmented mixed finite element method for the Biot problem with nonlinear permeability
- Hybrid Joint-Selective Optimization: Reduced-Space Levenberg-Marquardt Refinement of Low-Dimensional Parameters of Interest
- Mixed-Precision Computing for Scientific Discovery: Formats, Co-Design, and Responsible Approximation
- Riemannian optimization on low-rank tensor train manifolds for the Gross-Pitaevskii equation
- High Performance Computing of SDRE models with Discrete Kalman Filtering for Robust H∞-Controls
- Hard-Trace First-Order Residual Learning for Coupled Stokes-Brinkman-Darcy Flow
- Structure-preserving upwind Lagrange multiplier schemes for solid-state dewetting with a logarithmic Flory--Huggins potential
- CI-PINN: Causal Integral Physics-Informed Neural Network for Solving Evolution Equations
- Compressed Sensing with Quantized Tensor Trains (QTTs)