Cover Image

Implicit Bias of the JKO Scheme

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Halmos, Peter, Hanin, Boris
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Analysis of PDEs
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An Implicit GNN Solver for Poisson-like problems
by: Nastorg, Matthieu, et al.
Published: (2023)

Bayesian Inference with Deep Weakly Nonlinear Networks
by: Hanin, Boris, et al.
Published: (2024)

$PINN - a Domain Decomposition Method for Bayesian Physics-Informed Neural Networks
by: Figueres, Júlia Vicens, et al.
Published: (2025)

Conformal mapping based Physics-informed neural networks for designing neutral inclusions
by: Cho, Daehee, et al.
Published: (2025)

A novel framework for generalization of deep hidden physics models
by: Kag, Vijay, et al.
Published: (2024)

ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks
by: Wang, Yuelin, et al.
Published: (2022)

Quantitative Analysis of Molecular Transport in the Extracellular Space Using Physics-Informed Neural Network
by: Xie, Jiayi, et al.
Published: (2024)

Learning embeddings of non-linear PDEs: the Burgers' equation
by: Tarancón-Álvarez, Pedro, et al.
Published: (2026)

Latent Neural PDE Solver: a reduced-order modelling framework for partial differential equations
by: Li, Zijie, et al.
Published: (2024)

SPIKE: Stable Physics-Informed Kernel Evolution Method for Solving Hyperbolic Conservation Laws
by: Su, Hua, et al.
Published: (2025)

Physics-informed fine-tuning of foundation models for partial differential equations
by: Medvedev, Vlad, et al.
Published: (2026)

Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme
by: Persiianov, Mikhail, et al.
Published: (2025)

Generalized Logarithmic Sobolev Inequality by the JKO Scheme
by: Caillet, Thibault, et al.
Published: (2026)

From Monte Carlo to neural networks approximations of boundary value problems
by: Beznea, Lucian, et al.
Published: (2022)

Data assimilation and discrepancy modeling with shallow recurrent decoders
by: Bao, Yuxuan, et al.
Published: (2025)

PILD: Physics-Informed Learning via Diffusion
by: Zeng, Tianyi, et al.
Published: (2026)

General Explicit Network (GEN): A novel deep learning architecture for solving partial differential equations
by: Ma, Genwei, et al.
Published: (2026)

Smooth Piecewise Cutting for Neural Operator to Handle Discontinuities and Sharp Transitions
by: Dang, Ha, et al.
Published: (2026)

Learning Rate Transfer in Normalized Transformers
by: Shigida, Boris, et al.
Published: (2026)

Li-Yau-Hamilton Inequality on the JKO Scheme for the Granular-Medium Equation
by: Coudreuse, Fanch
Published: (2025)

Hermite Neural Network Simulation for Solving the 2D Schrodinger Equation
by: Parand, Kourosh, et al.
Published: (2024)

Improved Graph-based semi-supervised learning Schemes
by: Bozorgnia, Farid
Published: (2024)

Convergence of the fully discrete JKO scheme
by: Hraivoronska, Anastasiia, et al.
Published: (2025)

Efficient PINNs via Multi-Head Unimodular Regularization of the Solutions Space
by: Tarancón-Álvarez, Pedro, et al.
Published: (2025)

Adaptive control of reaction-diffusion PDEs via neural operator-approximated gain kernels
by: Bhan, Luke, et al.
Published: (2024)

On the Implicit Bias of Adam
by: Cattaneo, Matias D., et al.
Published: (2023)

Using Sinkhorn in the JKO scheme adds linear diffusion
by: Baradat, Aymeric, et al.
Published: (2025)

Numerical Schemes for Signature Kernels
by: Cass, Thomas, et al.
Published: (2025)

Deriving Transformer Architectures as Implicit Multinomial Regression
by: Actor, Jonas A., et al.
Published: (2025)

The Effect of Mini-Batch Noise on the Implicit Bias of Adam
by: Cattaneo, Matias D., et al.
Published: (2026)

A convergence rate for the entropic JKO scheme
by: Baradat, Aymeric, et al.
Published: (2026)

Deep Neural Nets as Hamiltonians
by: Winer, Mike, et al.
Published: (2025)

Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling
by: Halmos, Peter, et al.
Published: (2024)

Soliton profiles: Classical Numerical Schemes vs. Neural Network - Based Solvers
by: Haight, Chandler, et al.
Published: (2025)

Graph convolutional networks enable fast hemorrhagic stroke monitoring with electrical impedance tomography
by: Toivanen, J., et al.
Published: (2024)

Quantitative CLTs in Deep Neural Networks
by: Favaro, Stefano, et al.
Published: (2023)

Fisher information and continuity estimates for nonlinear but 1-homogeneous diffusive PDEs (via the JKO scheme)
by: Caillet, Thibault, et al.
Published: (2024)

Enhancing PINN Performance Through Lie Symmetry Group
by: Shah, Ali Haider, et al.
Published: (2025)

From Initial Data to Boundary Layers: Neural Networks for Nonlinear Hyperbolic Conservation Laws
by: Ciril, Igor, et al.
Published: (2025)

QED: An Open-Source Multi-Agent System for Generating Mathematical Proofs on Open Problems
by: An, Chenyang, et al.
Published: (2026)