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universal approximation

51 papers

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Also known as

UAP

Co-occurring keywords

neural network (6616) function approximation (319) recurrent neural network (1790) activation function (133) attention mechanism (3975) manifold learning (402) neural network architecture (362) neural network optimization (1293) convolutional neural network (4216) deep neural network (1801)

Papers

HyRNN: Hybrid Recurrent Neural Networks for Approximating Hybrid Dynamical Systems AAAI 2026
Continuum Attention for Neural Operators JMLR 2025
Deep Neural Network Approximation of Invariant Functions through Dynamical Systems JMLR 2024
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters NIPS 2024
On the Intrinsic Structures of Spiking Neural Networks JMLR 2024
Universal In-Context Approximation By Prompting Fully Recurrent Models NIPS 2024
Meta-Learning Universal Priors Using Non-Injective Change of Variables NIPS 2024
Rethinking 3D Convolution in $\ell_p$-norm Space NIPS 2024
Simple Cycle Reservoirs are Universal JMLR 2024
DE-HNN: An effective neural model for Circuit Netlist representation AISTATS 2024
Rethinking the Capacity of Graph Neural Networks for Branching Strategy NIPS 2024
Inverse M-Kernels for Linear Universal Approximators of Non-Negative Functions NIPS 2024
Light Unbalanced Optimal Transport NIPS 2024
Neural Oscillators are Universal NIPS 2023
Quasi-Equivalence between Width and Depth of Neural Networks JMLR 2023
Structure of universal formulas NIPS 2023
Minimal Width for Universal Property of Deep RNN JMLR 2023
Universal Approximation Property of Invertible Neural Networks JMLR 2023
Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions NIPS 2023
Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation ICML 2023
Probabilistic Invariant Learning with Randomized Linear Classifiers NIPS 2023
Universality and Limitations of Prompt Tuning NIPS 2023
Theoretical Analysis of the Inductive Biases in Deep Convolutional Networks NIPS 2023
Learning on Manifolds: Universal Approximations Properties using Geometric Controllability Conditions for Neural ODEs L4DC 2023
Recurrent Neural Networks and Universal Approximation of Bayesian Filters AISTATS 2023