Saved in:
| Main Authors: | Jahn, T., Chemseddine, J., Hagemann, P., Wald, C., Steidl, G. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.23215 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching
by: Chemseddine, Jannis, et al.
Published: (2024)
by: Chemseddine, Jannis, et al.
Published: (2024)
Neural Sampling from Boltzmann Densities: Fisher-Rao Curves in the Wasserstein Geometry
by: Chemseddine, Jannis, et al.
Published: (2024)
by: Chemseddine, Jannis, et al.
Published: (2024)
Sampling via Stochastic Interpolants by Langevin-based Velocity and Initialization Estimation in Flow ODEs
by: Duan, Chenguang, et al.
Published: (2026)
by: Duan, Chenguang, et al.
Published: (2026)
Adapting Noise to Data: Generative Flows from 1D Processes
by: Chemseddine, Jannis, et al.
Published: (2025)
by: Chemseddine, Jannis, et al.
Published: (2025)
Fast Summation of Radial Kernels via QMC Slicing
by: Hertrich, Johannes, et al.
Published: (2024)
by: Hertrich, Johannes, et al.
Published: (2024)
Unsupervised Ground Metric Learning
by: Auffenberg, Janis, et al.
Published: (2025)
by: Auffenberg, Janis, et al.
Published: (2025)
Self-Aware Markov Models for Discrete Reasoning
by: Kornhardt, Gregor, et al.
Published: (2026)
by: Kornhardt, Gregor, et al.
Published: (2026)
Scalable Signature Kernel Computations for Long Time Series via Local Neumann Series Expansions
by: Tamayo-Rios, Matthew, et al.
Published: (2025)
by: Tamayo-Rios, Matthew, et al.
Published: (2025)
Sharp Convergence Rates for Matching Pursuit
by: Klusowski, Jason M., et al.
Published: (2023)
by: Klusowski, Jason M., et al.
Published: (2023)
Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning
by: Dong, Yijun, et al.
Published: (2024)
by: Dong, Yijun, et al.
Published: (2024)
CFO: Learning Continuous-Time PDE Dynamics via Flow-Matched Neural Operators
by: Hou, Xianglong, et al.
Published: (2025)
by: Hou, Xianglong, et al.
Published: (2025)
GeoFunFlow-3D: A Physics-Guided Generative Flow Matching Framework for High-Fidelity 3D Aerodynamic Inference over Complex Geometries
by: Jiang, Ruiling, et al.
Published: (2026)
by: Jiang, Ruiling, et al.
Published: (2026)
Exact Gaussian Moment Matching for Residual Networks: a Second-Order Method
by: Kuang, Simon, et al.
Published: (2026)
by: Kuang, Simon, et al.
Published: (2026)
A Hybridizable Neural Time Integrator for Stable Autoregressive Forecasting
by: Kinch, Brooks, et al.
Published: (2026)
by: Kinch, Brooks, et al.
Published: (2026)
Identifying Best Practice Melting Patterns in Induction Furnaces: A Data-Driven Approach Using Time Series KMeans Clustering and Multi-Criteria Decision Making
by: Howard, Daniel Anthony, et al.
Published: (2024)
by: Howard, Daniel Anthony, et al.
Published: (2024)
TINNs: Time-Induced Neural Networks for Solving Time-Dependent PDEs
by: Dai, Chen-Yang, et al.
Published: (2026)
by: Dai, Chen-Yang, et al.
Published: (2026)
GenUQ: Predictive Uncertainty Estimates via Generative Hyper-Networks
by: Yen, Tian Yu, et al.
Published: (2025)
by: Yen, Tian Yu, et al.
Published: (2025)
Hamiltonian Matching for Symplectic Neural Integrators
by: Canizares, Priscilla, et al.
Published: (2024)
by: Canizares, Priscilla, et al.
Published: (2024)
Geometry-Preserving Encoder/Decoder in Latent Generative Models
by: Lee, Wonjun, et al.
Published: (2025)
by: Lee, Wonjun, et al.
Published: (2025)
A Microstructure-based Graph Neural Network for Accelerating Multiscale Simulations
by: Storm, J., et al.
Published: (2024)
by: Storm, J., et al.
Published: (2024)
Flow Matching: Markov Kernels, Stochastic Processes and Transport Plans
by: Wald, Christian, et al.
Published: (2025)
by: Wald, Christian, et al.
Published: (2025)
Parallel-in-Time Probabilistic Numerical ODE Solvers
by: Bosch, Nathanael, et al.
Published: (2023)
by: Bosch, Nathanael, et al.
Published: (2023)
Inference-Time Alignment for Diffusion Models via Variationally Stable Doob's Matching
by: Chang, Jinyuan, et al.
Published: (2026)
by: Chang, Jinyuan, et al.
Published: (2026)
Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averaging
by: Banerjee, Amartya, et al.
Published: (2024)
by: Banerjee, Amartya, et al.
Published: (2024)
Generalized Canonical Polyadic Tensor Decompositions with General Symmetry
by: Mulrooney, Alex, et al.
Published: (2026)
by: Mulrooney, Alex, et al.
Published: (2026)
Parallel-in-Time Solutions with Random Projection Neural Networks
by: Betcke, Marta M., et al.
Published: (2024)
by: Betcke, Marta M., et al.
Published: (2024)
Time Extrapolation with Graph Convolutional Autoencoder and Tensor Train Decomposition
by: Chen, Yuanhong, et al.
Published: (2025)
by: Chen, Yuanhong, et al.
Published: (2025)
Latent Neural Operator Pretraining for Solving Time-Dependent PDEs
by: Wang, Tian, et al.
Published: (2024)
by: Wang, Tian, et al.
Published: (2024)
Stochastic Optimal Control Matching
by: Domingo-Enrich, Carles, et al.
Published: (2023)
by: Domingo-Enrich, Carles, et al.
Published: (2023)
ZNO: Stable Rational Neural Operators in the Z-Domain for Discrete-Time Dynamics
by: Zhu, Xianli, et al.
Published: (2026)
by: Zhu, Xianli, et al.
Published: (2026)
Leveraging Real-Time Data Analysis and Multiple Kernel Learning for Manufacturing of Innovative Steels
by: Rannetbauer, Wolfgang, et al.
Published: (2025)
by: Rannetbauer, Wolfgang, et al.
Published: (2025)
Machine Learning Algorithms to Assess Site Closure Time Frames for Soil and Groundwater Contamination
by: Le, Vu-Anh, et al.
Published: (2024)
by: Le, Vu-Anh, et al.
Published: (2024)
Generating synthetic data for neural operators
by: Hasani, Erisa, et al.
Published: (2024)
by: Hasani, Erisa, et al.
Published: (2024)
Generative Adversarial Reduced Order Modelling
by: Coscia, Dario, et al.
Published: (2023)
by: Coscia, Dario, et al.
Published: (2023)
Investigating the Ability of PINNs To Solve Burgers' PDE Near Finite-Time BlowUp
by: Kumar, Dibyakanti, et al.
Published: (2023)
by: Kumar, Dibyakanti, et al.
Published: (2023)
Generalizing the SINDy approach with nested neural networks
by: Fiorini, Camilla, et al.
Published: (2024)
by: Fiorini, Camilla, et al.
Published: (2024)
Lipschitz-Guided Design of Interpolation Schedules in Generative Models
by: Chen, Yifan, et al.
Published: (2025)
by: Chen, Yifan, et al.
Published: (2025)
Efficient Differentiable Approximation of Generalized Low-rank Regularization
by: Li, Naiqi, et al.
Published: (2025)
by: Li, Naiqi, et al.
Published: (2025)
Interpretable Spatial-Temporal Fusion Transformers: Multi-Output Prediction for Parametric Dynamical Systems with Time-Varying Inputs
by: Sun, Shuwen, et al.
Published: (2025)
by: Sun, Shuwen, et al.
Published: (2025)
Generative Feature Training of Thin 2-Layer Networks
by: Hertrich, Johannes, et al.
Published: (2024)
by: Hertrich, Johannes, et al.
Published: (2024)
Similar Items
-
Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching
by: Chemseddine, Jannis, et al.
Published: (2024) -
Neural Sampling from Boltzmann Densities: Fisher-Rao Curves in the Wasserstein Geometry
by: Chemseddine, Jannis, et al.
Published: (2024) -
Sampling via Stochastic Interpolants by Langevin-based Velocity and Initialization Estimation in Flow ODEs
by: Duan, Chenguang, et al.
Published: (2026) -
Adapting Noise to Data: Generative Flows from 1D Processes
by: Chemseddine, Jannis, et al.
Published: (2025) -
Fast Summation of Radial Kernels via QMC Slicing
by: Hertrich, Johannes, et al.
Published: (2024)