:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Narayanaswami, Sai Kiran, Srinivasan, Gopalakrishnan, Ravindran, Balaraman
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Numerical Analysis Neural and Evolutionary Computing
Online Access:	https://arxiv.org/abs/2412.00408
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Efficient Design of Compliant Mechanisms Using Multi-Objective Optimization
by: Humer, Alexander, et al.
Published: (2025)

Approximating Matrix Functions with Deep Neural Networks and Transformers
by: Padmanabhan, Rahul, et al.
Published: (2026)

Expressivity and Approximation Properties of Deep Neural Networks with ReLU$^k$ Activation
by: He, Juncai, et al.
Published: (2023)

SO-PIFRNN: Self-optimization physics-informed Fourier-features randomized neural network for solving partial differential equations
by: Linghu, Jiale, et al.
Published: (2025)

From LIF to QIF: Toward Differentiable Spiking Neurons for Scientific Machine Learning
by: Wan, Ruyin, et al.
Published: (2025)

A Wachspress-based transfinite formulation for exactly enforcing Dirichlet boundary conditions on convex polygonal domains in physics-informed neural networks
by: Sukumar, N., et al.
Published: (2026)

Approximation Rates in Besov Norms and Sample-Complexity of Kolmogorov-Arnold Networks with Residual Connections
by: Kratsios, Anastasis, et al.
Published: (2025)

Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of Experts
by: Kratsios, Anastasis, et al.
Published: (2024)

Robust Parameter and State Estimation in Multiscale Neuronal Systems Using Physics-Informed Neural Networks
by: Wei, Changliang, et al.
Published: (2026)

Towards an Algebraic Framework For Approximating Functions Using Neural Network Polynomials
by: Rafi, Shakil, et al.
Published: (2024)

rKAN: Rational Kolmogorov-Arnold Networks
by: Aghaei, Alireza Afzal
Published: (2024)

Semialgebraic Neural Networks: From roots to representations
by: Mis, S. David, et al.
Published: (2025)

Goat Optimization Algorithm: A Novel Bio-Inspired Metaheuristic for Global Optimization
by: Nozari, Hamed, et al.
Published: (2025)

A third-order finite difference weighted essentially non-oscillatory scheme with shallow neural network
by: Park, Kwanghyuk, et al.
Published: (2024)

Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution
by: Perez, Sarah, et al.
Published: (2023)

HiPreNets: High-Precision Neural Networks through Progressive Training
by: Mulle, Ethan, et al.
Published: (2025)

A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder
by: Kim, Youngkyu, et al.
Published: (2020)

Deep greedy unfolding: Sorting out argsorting in greedy sparse recovery algorithms
by: Mohammad-Taheri, Sina, et al.
Published: (2025)

Heuristic Solution to Joint Deployment and Beamforming Design for STAR-RIS Aided Networks
by: Yan, Bai, et al.
Published: (2024)

Structured and Balanced Multi-Component and Multi-Layer Neural Networks
by: Zhang, Shijun, et al.
Published: (2024)

Universality and approximation bounds for echo state networks with random weights
by: Li, Zhen, et al.
Published: (2022)

Randomized Forward Mode Gradient for Spiking Neural Networks in Scientific Machine Learning
by: Wan, Ruyin, et al.
Published: (2024)

Physics-Informed Neural Network based inverse framework for time-fractional differential equations for rheology
by: Thakur, Sukirt, et al.
Published: (2024)

Linking Microscopic and Macroscopic Models for Evolution: Markov Chain Network Training and Conservation Law Approximations
by: Melnik, Roderick V. N.
Published: (2007)

Chebyshev Feature Neural Network for Accurate Function Approximation
by: Xu, Zhongshu, et al.
Published: (2024)

Is In-Context Universality Enough? MLPs are Also Universal In-Context
by: Kratsios, Anastasis, et al.
Published: (2025)

Stability and Discretization Error of State Space Model Neural Operators
by: Bendahi, Abderrahim, et al.
Published: (2026)

TensorGPT: Efficient Compression of Large Language Models based on Tensor-Train Decomposition
by: Xu, Mingxue, et al.
Published: (2023)

Splitting physics-informed neural networks for inferring the dynamics of integer- and fractional-order neuron models
by: Shekarpaz, Simin, et al.
Published: (2023)

KAN versus MLP on Irregular or Noisy Functions
by: Zeng, Chen, et al.
Published: (2024)

Activations Through Extensions: A Framework To Boost Performance Of Neural Networks
by: Kamanchi, Chandramouli, et al.
Published: (2024)

Do physics-informed neural networks (PINNs) need to be deep? Shallow PINNs using the Levenberg-Marquardt algorithm
by: Shahab, Muhammad Luthfi, et al.
Published: (2026)

Solving Sparse Finite Element Problems on Neuromorphic Hardware
by: Theilman, Bradley H., et al.
Published: (2025)

A Practitioner's Guide to Kolmogorov-Arnold Networks
by: Noorizadegan, Amir, et al.
Published: (2025)

Intrinsic Numerical Robustness and Fault Tolerance in a Neuromorphic Algorithm for Scientific Computing
by: Theilman, Bradley H., et al.
Published: (2026)

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

PASCAL: Precise and Efficient ANN- SNN Conversion using Spike Accumulation and Adaptive Layerwise Activation
by: Ramesh, Pranav, et al.
Published: (2025)

Scaling Equilibrium Propagation to Deeper Neural Network Architectures
by: Elayedam, Sankar Vinayak, et al.
Published: (2025)

Bridging the Gap Between Approximation and Learning via Optimal Approximation by ReLU MLPs of Maximal Regularity
by: Hong, Ruiyang, et al.
Published: (2024)

Sinc Kolmogorov-Arnold network and its application for solving PDEs with singularities
by: Yu, Tianchi, et al.
Published: (2024)