Neural Network Approach to Stochastic Dynamics for Smooth Multimodal Density Estimation
Fuente:
arXiv
Saved in:
| Main Authors: | Zarezadeh, Z., Zarezadeh, N. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Quantum Neural Network Restatement of Markov Jump Process
by: Zarezadeh, Z., et al.
Published: (2025)
by: Zarezadeh, Z., et al.
Published: (2025)
Neural Networks: According to the Principles of Grassmann Algebra
by: Zarezadeh, Z., et al.
Published: (2025)
by: Zarezadeh, Z., et al.
Published: (2025)
Smoothness Adaptivity in Constant-Depth Neural Networks: Optimal Rates via Smooth Activations
by: Liu, Yuhao, et al.
Published: (2026)
by: Liu, Yuhao, et al.
Published: (2026)
Stochastic Fractional Neural Operators: A Symmetrized Approach to Modeling Turbulence in Complex Fluid Dynamics
by: Santos, Rômulo Damasclin Chaves dos, et al.
Published: (2025)
by: Santos, Rômulo Damasclin Chaves dos, et al.
Published: (2025)
Estimating condition number with Graph Neural Networks
by: Carson, Erin, et al.
Published: (2026)
by: Carson, Erin, et al.
Published: (2026)
Unified Stochastic Framework for Neural Network Quantization and Pruning
by: Zhang, Haoyu, et al.
Published: (2024)
by: Zhang, Haoyu, et al.
Published: (2024)
Convergence of Stochastic Gradient Methods for Wide Two-Layer Physics-Informed Neural Networks
by: Jin, Bangti, et al.
Published: (2025)
by: Jin, Bangti, et al.
Published: (2025)
Learning Stochastic Dynamical Systems with Structured Noise
by: Guo, Ziheng, et al.
Published: (2025)
by: Guo, Ziheng, et al.
Published: (2025)
Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks
by: Schotthöfer, Steffen, et al.
Published: (2025)
by: Schotthöfer, Steffen, et al.
Published: (2025)
$ε$-rank and the Staircase Phenomenon: New Insights into Neural Network Training Dynamics
by: Yang, Jiang, et al.
Published: (2024)
by: Yang, Jiang, et al.
Published: (2024)
Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs
by: Krach, Florian, et al.
Published: (2022)
by: Krach, Florian, et al.
Published: (2022)
Computation-Aware Kalman Filtering and Smoothing
by: Pförtner, Marvin, et al.
Published: (2024)
by: Pförtner, Marvin, et al.
Published: (2024)
Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models
by: Saporiti, Riccardo, et al.
Published: (2026)
by: Saporiti, Riccardo, et al.
Published: (2026)
Empirical Density Estimation based on Spline Quasi-Interpolation with applications to Copulas clustering modeling
by: Tamborrino, Cristiano, et al.
Published: (2024)
by: Tamborrino, Cristiano, et al.
Published: (2024)
Learning from Linear Algebra: A Graph Neural Network Approach to Preconditioner Design for Conjugate Gradient Solvers
by: Trifonov, Vladislav, et al.
Published: (2024)
by: Trifonov, Vladislav, et al.
Published: (2024)
Radial Müntz-Szász Networks: Neural Architectures with Learnable Power Bases for Multidimensional Singularities
by: N'guessan, Gnankan Landry Regis, et al.
Published: (2026)
by: N'guessan, Gnankan Landry Regis, et al.
Published: (2026)
Multivariate Density Estimation via Variance-Reduced Sketching
by: Peng, Yifan, et al.
Published: (2024)
by: Peng, Yifan, et al.
Published: (2024)
Multigrade Neural Network Approximation
by: Zhang, Shijun, et al.
Published: (2026)
by: Zhang, Shijun, et al.
Published: (2026)
Determinant Estimation under Memory Constraints and Neural Scaling Laws
by: Ameli, Siavash, et al.
Published: (2025)
by: Ameli, Siavash, et al.
Published: (2025)
THINNs: Thermodynamically Informed Neural Networks
by: Castro, Javier, et al.
Published: (2025)
by: Castro, Javier, et al.
Published: (2025)
Preconditioning for Physics-Informed Neural Networks
by: Liu, Songming, et al.
Published: (2024)
by: Liu, Songming, et al.
Published: (2024)
Discrete Differential Principle for Continuous Smooth Function Representation
by: Wang, Guoyou, et al.
Published: (2025)
by: Wang, Guoyou, et al.
Published: (2025)
A Dimensionality Reduction Approach for Convolutional Neural Networks
by: Meneghetti, Laura, et al.
Published: (2021)
by: Meneghetti, Laura, et al.
Published: (2021)
Dual-Balancing for Physics-Informed Neural Networks
by: Zhou, Chenhong, et al.
Published: (2025)
by: Zhou, Chenhong, et al.
Published: (2025)
Operator Learning for Smoothing and Forecasting
by: Calvello, Edoardo, et al.
Published: (2026)
by: Calvello, Edoardo, et al.
Published: (2026)
Deep Eigenspace Network for Parametric Non-self-adjoint Eigenvalue Problems
by: Li, H., et al.
Published: (2025)
by: Li, H., et al.
Published: (2025)
Tensor Decomposition Meets RKHS: Efficient Algorithms for Smooth and Misaligned Data
by: Larsen, Brett W., et al.
Published: (2024)
by: Larsen, Brett W., et al.
Published: (2024)
E-PINNs: Epistemic Physics-Informed Neural Networks
by: Jacob, Bruno, et al.
Published: (2025)
by: Jacob, Bruno, et al.
Published: (2025)
Decentralized Neural Networks for Robust and Scalable Eigenvalue Computation
by: Katende, Ronald
Published: (2024)
by: Katende, Ronald
Published: (2024)
Deep NURBS -- Admissible Physics-informed Neural Networks
by: Saidaoui, Hamed, et al.
Published: (2022)
by: Saidaoui, Hamed, et al.
Published: (2022)
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)
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)
GenUQ: Predictive Uncertainty Estimates via Generative Hyper-Networks
by: Yen, Tian Yu, et al.
Published: (2025)
by: Yen, Tian Yu, et al.
Published: (2025)
Bayesian Physics Informed Neural Networks for Linear Inverse problems
by: Mohammad-Djafari, Ali
Published: (2025)
by: Mohammad-Djafari, Ali
Published: (2025)
Deep Neural Network Solutions for Oscillatory Fredholm Integral Equations
by: Jiang, Jie, et al.
Published: (2024)
by: Jiang, Jie, et al.
Published: (2024)
Physics-embedded Fourier Neural Network for Partial Differential Equations
by: Xu, Qingsong, et al.
Published: (2024)
by: Xu, Qingsong, et al.
Published: (2024)
Graph Neural Networks for Community Detection in Graph Signal Analysis
by: Cavoretto, Roberto, et al.
Published: (2026)
by: Cavoretto, Roberto, et al.
Published: (2026)
Parareal Neural Networks Emulating a Parallel-in-time Algorithm
by: Lee, Chang-Ock, et al.
Published: (2021)
by: Lee, Chang-Ock, et al.
Published: (2021)
Transformed Physics-Informed Neural Networks for The Convection-Diffusion Equation
by: Guan, Jiajing, et al.
Published: (2024)
by: Guan, Jiajing, et al.
Published: (2024)
Point Source Identification Using Singularity Enriched Neural Networks
by: Hu, Tianhao, et al.
Published: (2024)
by: Hu, Tianhao, et al.
Published: (2024)
Similar Items
-
Quantum Neural Network Restatement of Markov Jump Process
by: Zarezadeh, Z., et al.
Published: (2025) -
Neural Networks: According to the Principles of Grassmann Algebra
by: Zarezadeh, Z., et al.
Published: (2025) -
Smoothness Adaptivity in Constant-Depth Neural Networks: Optimal Rates via Smooth Activations
by: Liu, Yuhao, et al.
Published: (2026) -
Stochastic Fractional Neural Operators: A Symmetrized Approach to Modeling Turbulence in Complex Fluid Dynamics
by: Santos, Rômulo Damasclin Chaves dos, et al.
Published: (2025) -
Estimating condition number with Graph Neural Networks
by: Carson, Erin, et al.
Published: (2026)