Saved in:
| Main Authors: | Murray, Ryan, Pickarski, Adam |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.02433 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
On the continuum limit of t-SNE for data visualization
by: Calder, Jeff, et al.
Published: (2026)
by: Calder, Jeff, et al.
Published: (2026)
Large data limits and scaling laws for tSNE
by: Murray, Ryan, et al.
Published: (2024)
by: Murray, Ryan, et al.
Published: (2024)
Regularity of Solutions to Beckmann's Parametric Optimal Transport
by: Gottschalk, Hanno, et al.
Published: (2026)
by: Gottschalk, Hanno, et al.
Published: (2026)
The Multimarginal Optimal Transport Formulation of Adversarial Multiclass Classification
by: Trillos, Nicolas Garcia, et al.
Published: (2022)
by: Trillos, Nicolas Garcia, et al.
Published: (2022)
Harmonic Control Lyapunov Barrier Functions for Constrained Optimal Control with Reach-Avoid Specifications
by: Mukherjee, Amartya, et al.
Published: (2023)
by: Mukherjee, Amartya, et al.
Published: (2023)
Interaction-Force Transport Gradient Flows
by: Gladin, Egor, et al.
Published: (2024)
by: Gladin, Egor, et al.
Published: (2024)
Efficient Numerical Wave Propagation Enhanced By An End-to-End Deep Learning Model
by: Kaiser, Luis, et al.
Published: (2024)
by: Kaiser, Luis, et al.
Published: (2024)
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery
by: Yu, Yue, et al.
Published: (2024)
by: Yu, Yue, et al.
Published: (2024)
Global Well-posedness and Convergence Analysis of Score-based Generative Models via Sharp Lipschitz Estimates
by: Mooney, Connor, et al.
Published: (2024)
by: Mooney, Connor, et al.
Published: (2024)
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input
by: Chen, Ziang, et al.
Published: (2024)
by: Chen, Ziang, et al.
Published: (2024)
Improved Graph-based semi-supervised learning Schemes
by: Bozorgnia, Farid
Published: (2024)
by: Bozorgnia, Farid
Published: (2024)
Solving the Poisson Equation with Dirichlet data by shallow ReLU$^α$-networks: A regularity and approximation perspective
by: Vaishampayan, Malhar, et al.
Published: (2024)
by: Vaishampayan, Malhar, et al.
Published: (2024)
Kernel Approximation of Fisher-Rao Gradient Flows
by: Zhu, Jia-Jie, et al.
Published: (2024)
by: Zhu, Jia-Jie, et al.
Published: (2024)
A Physics Informed Neural Network (PINN) Methodology for Coupled Moving Boundary PDEs
by: Kathane, Shivprasad, et al.
Published: (2024)
by: Kathane, Shivprasad, et al.
Published: (2024)
Learning functional components of PDEs from data using neural networks
by: Loman, Torkel E., et al.
Published: (2026)
by: Loman, Torkel E., et al.
Published: (2026)
Partial Differential Equations in the Age of Machine Learning: A Critical Synthesis of Classical, Machine Learning, and Hybrid Methods
by: Nooraiepour, Mohammad, et al.
Published: (2026)
by: Nooraiepour, Mohammad, et al.
Published: (2026)
Minimax Rates for the Estimation of Eigenpairs of Weighted Laplace-Beltrami Operators on Manifolds
by: Trillos, Nicolás García, et al.
Published: (2025)
by: Trillos, Nicolás García, et al.
Published: (2025)
Generalization Error Bounds for Picard-Type Operator Learning in Nonlinear Parabolic PDEs
by: Taniguchi, Koichi, et al.
Published: (2026)
by: Taniguchi, Koichi, et al.
Published: (2026)
Is Zero-Shot Super-Resolution Possible in Operator Learning?
by: Subedi, Unique, et al.
Published: (2026)
by: Subedi, Unique, et al.
Published: (2026)
The emergence of clusters in self-attention dynamics
by: Geshkovski, Borjan, et al.
Published: (2023)
by: Geshkovski, Borjan, et al.
Published: (2023)
Learning PDE Solvers with Physics and Data: A Unifying View of Physics-Informed Neural Networks and Neural Operators
by: Dai, Yilong, et al.
Published: (2026)
by: Dai, Yilong, 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)
Double Coupling Architecture and Training Method for Optimization Problems of Differential Algebraic Equations with Parameters
by: Yang, Wenqiang, et al.
Published: (2026)
by: Yang, Wenqiang, et al.
Published: (2026)
Deep Learning-Enhanced Calibration of the Heston Model: A Unified Framework
by: Zadgar, Arman, et al.
Published: (2025)
by: Zadgar, Arman, et al.
Published: (2025)
Stiff Transfer Learning for Physics-Informed Neural Networks
by: Seiler, Emilien, et al.
Published: (2025)
by: Seiler, Emilien, et al.
Published: (2025)
Trace Regularity PINNs: Enforcing $\mathrm{H}^{\frac{1}{2}}(\partial Ω)$ for Boundary Data
by: Kim, Doyoon, et al.
Published: (2025)
by: Kim, Doyoon, et al.
Published: (2025)
Wasserstein Bounds for generative diffusion models with Gaussian tail targets
by: Wang, Xixian, et al.
Published: (2024)
by: Wang, Xixian, et al.
Published: (2024)
Barron Space Representations for Elliptic PDEs with Homogeneous Boundary Conditions
by: Chen, Ziang, et al.
Published: (2025)
by: Chen, Ziang, et al.
Published: (2025)
Generalization Bounds for Physics-Informed Neural Networks for the Incompressible Navier-Stokes Equations
by: Andre-Sloan, Sebastien, et al.
Published: (2026)
by: Andre-Sloan, Sebastien, et al.
Published: (2026)
DeepRitzSplit Neural Operator for Phase-Field Models via Energy Splitting
by: Huang, Chih-Kang, et al.
Published: (2026)
by: Huang, Chih-Kang, et al.
Published: (2026)
Unified generalization analysis for physics informed neural networks
by: Hashimoto, Yuka, et al.
Published: (2026)
by: Hashimoto, Yuka, et al.
Published: (2026)
Rigorous Error Certification for Neural PDE Solvers: From Empirical Residuals to Solution Guarantees
by: Mukherjee, Amartya, et al.
Published: (2026)
by: Mukherjee, Amartya, et al.
Published: (2026)
Singularity Formation: Synergy in Theoretical, Numerical and Machine Learning Approaches
by: Wang, Yixuan
Published: (2026)
by: Wang, Yixuan
Published: (2026)
Regularity of Second-Order Elliptic PDEs in Spectral Barron Spaces
by: Chen, Ziang, et al.
Published: (2026)
by: Chen, Ziang, 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)
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)
Optimal Embedding Dimension for Sparse Subspace Embeddings
by: Chenakkod, Shabarish, et al.
Published: (2023)
by: Chenakkod, Shabarish, et al.
Published: (2023)
Space-time deep neural network approximations for high-dimensional partial differential equations
by: Hornung, Fabian, et al.
Published: (2020)
by: Hornung, Fabian, et al.
Published: (2020)
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)
Kinetic theory for Transformers and the lost-in-the-middle phenomenon
by: Duerinckx, Mitia, et al.
Published: (2026)
by: Duerinckx, Mitia, et al.
Published: (2026)
Similar Items
-
On the continuum limit of t-SNE for data visualization
by: Calder, Jeff, et al.
Published: (2026) -
Large data limits and scaling laws for tSNE
by: Murray, Ryan, et al.
Published: (2024) -
Regularity of Solutions to Beckmann's Parametric Optimal Transport
by: Gottschalk, Hanno, et al.
Published: (2026) -
The Multimarginal Optimal Transport Formulation of Adversarial Multiclass Classification
by: Trillos, Nicolas Garcia, et al.
Published: (2022) -
Harmonic Control Lyapunov Barrier Functions for Constrained Optimal Control with Reach-Avoid Specifications
by: Mukherjee, Amartya, et al.
Published: (2023)