math.NA

Papers

• The complexity of bit retrieval (2016)
  Veit Elser
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• Successive Projection Algorithm Robust to Outliers (2019)
  Nicolas Gillis
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• Projection techniques to update the truncated SVD of evolving matrices (2020)
  Vassilis Kalantzis et al.
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• Nonlinear Least Squares for Large-Scale Machine Learning using Stochastic Jacobian Estimates (2021)
  Johannes J. Brust
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• Fast Single-Core K-Nearest Neighbor Graph Computation (2021)
  Dan Kluser et al.
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• Johnson-Lindenstrauss embeddings for noisy vectors -- taking advantage of the noise (2022)
  Zhen Shao
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• Arithmetical Binary Decision Tree Traversals (2024)
  Jinxiong Zhang
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• A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equations (2026)
  Shu Liu et al.
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• Message-Passing GNNs Fail to Approximate Sparse Triangular Factorizations (2026)
  Vladislav Trifonov et al.
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• Hybrid least squares for learning functions from highly noisy data (2026)
  Ben Adcock et al.
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• Fredholm Neural Networks for inverse problems in elliptic PDEs (2026)
  Kyriakos C. Georgiou et al.
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• Search for Z/2 eigenfunctions on the sphere using machine learning (2025)
  Andriy Haydys et al.
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• ZORMS-LfD: Learning from Demonstrations with Zeroth-Order Random Matrix Search (2025)
  Olivia Dry et al.
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• Fast OTSU Thresholding Using Bisection Method (2025)
  Sai Varun Kodathala
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• Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators (2026)
  Gianluca Fabiani et al.
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• A first-order method for constrained nonconvex-nonconcave minimax optimization (2026)
  Zhaosong Lu et al.
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• Solving the Offline and Online Min-Max Problem of Non-smooth Submodular-Concave Functions: A Zeroth-Order Approach (2026)
  Amir Ali Farzin et al.
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• TorchLean: Formalizing Neural Networks in Lean (2026)
  Robert Joseph George et al.
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• Multidimensional Task Learning: A Unified Tensor Framework for Computer Vision Tasks (2026)
  Alaa El Ichi et al.
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• Towards Universal Convergence of Backward Error in Linear System Solvers (2026)
  Micha{\l} Derezi\'nski et al.
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• Complex Stochastic Gradient Descent and Directional Bias in Reproducing Kernel Hilbert Spaces (2026)
  Natanael Alpay et al.
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• SURGE: Approximation and Training Free Particle Filter for Diffusion Surrogate (2026)
  Lifu Wei et al.
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• Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approximations (2026)
  Shuang Chen et al.
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• Expand More, Shrink Less: Shaping Effective-Rank Dynamics for Dense Scaling in Recommendation (2026)
  Guoming Li et al.
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• Coupling-Robust Accuracy in Multiphysics Physics Informed Neural Networks via Kronecker-Preconditioned Optimization (2026)
  Youngjae Park et al.
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• Training-Free Looped Transformers (2026)
  Lizhang Chen et al.
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• WINO: A Weak-Form Physics Informed Neural Operator for Hyperelasticity on Variable Domains (2026)
  Bokai Zhu et al.
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• IV-Net: A neural network for elliptic PDEs with random and highly varying coefficients (2026)
  Shan Zhong et al.
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• Random Neural Network Expressivity for Non-Linear Partial Differential Equations (2026)
  Muhammed Ali Mehmood et al.
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• Leveraging Gauge Freedom for Learning Non-Gradient Population Dynamics of Stochastic Systems (2026)
  Jules Berman et al.
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• Autoregression-Free Neural Operators for Time-Dependent PDEs (2026)
  Jiaquan Zhang et al.
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• Branched Signature Kernel Solvers for ODEs with rough Single-Trajectory signals (2026)
  Munawar Ali et al.
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• Fuzzy PyTorch: Rapid Numerical Variability Evaluation for Deep Learning Models (2026)
  In\'es Gonzalez-Pepe et al.
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• Two-Parameter Flows for Learning Population Dynamics of Physical Systems (2026)
  Paul Schwerdtner et al.
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• Classification and detection of multiple UAVs using rational Gaussian wavelet neural networks (2026)
  Ungv\'ari Gerg\H{o} et al.
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• Semigroup Consistency as a Diagnostic for Learned Physics Simulators (2026)
  Lennon J. Shikhman
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• Recursive Flow Matching (2026)
  Jiahe Huang et al.
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• Manifold-based Algorithms for the Hadamard Decomposition (2026)
  Nicolas Gillis et al.
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• Ensemble Score Filtering for Real-Data Energy Consumption Forecast Correction (2026)
  Ruoyu Hu et al.
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• Stochastic Lifting for Generating Trajectories of Stochastic Physical Systems (2026)
  Jules Berman et al.
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• Kernel-based potential mean-field games with unbiased random Fourier $U$-statistics (2026)
  Yumiharu Nakano
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• Deep Adaptive Dimension Reduction for Bayesian Inference in Inverse Problems (2026)
  Yueyang Wang et al.
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