numerical solver

Few-Step Diffusion Sampling Through Instance-Aware Discretizations CVPR 2026 Accelerating Neural ODEs: A Variational Formulation-based Approach ICLR 2025 Efficient Training of Neural Fractional-Order Differential Equation via Adjoint Backpropagation AAAI 2025 FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing ICML 2025 Personal Travel Solver: A Preference-Driven LLM-Solver System for Travel Planning ACL 2025 Semialgebraic Neural Networks: From roots to representations ICLR 2025 AttNS: Attention-Inspired Numerical Solving For Limited Data Scenarios ICML 2024 Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees NeurIPS 2024 RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks NeurIPS 2024 Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations AAAI 2023 M2N: Mesh Movement Networks for PDE Solvers NeurIPS 2022 MAgNet: Mesh Agnostic Neural PDE Solver NeurIPS 2022 Message Passing Neural PDE Solvers ICLR 2022 Optimization for Classical Machine Learning Problems on the GPU AAAI 2022 "Hey, that’s not an ODE": Faster ODE Adjoints via Seminorms ICML 2021 Learning Algebraic Multigrid Using Graph Neural Networks ICML 2020 Learning Differential Equations that are Easy to Solve NeurIPS 2020 Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers NeurIPS 2020 Learning to Optimize Multigrid PDE Solvers ICML 2019 Probabilistic Linear Multistep Methods NeurIPS 2016