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universal approximation

75 papers

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Co-occurring keywords · papers mentioning both

neural network (9) function approximation (9) recurrent neural network (7) approximation theory (6) activation function (6) neural network optimization (5) neural network architecture (5) convolutional neural network (4) deep neural network (4) relu network (4)

Papers

End-to-End Deep Learning for Predicting Metric Space-Valued Outputs JMLR 2026 HyRNN: Hybrid Recurrent Neural Networks for Approximating Hybrid Dynamical Systems AAAI 2026 Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations ICML 2025 Approximation to Smooth Functions by Low-Rank Swish Networks ICML 2025 Continuum Attention for Neural Operators JMLR 2025 Expressivity of Neural Networks with Random Weights and Learned Biases ICLR 2025 Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency ICLR 2025 Fundamental Limits of Visual Autoregressive Transformers: Universal Approximation Abilities ICML 2025 Generalization, Expressivity, and Universality of Graph Neural Networks on Attributed Graphs ICLR 2025 Looped ReLU MLPs May Be All You Need as Practical Programmable Computers AISTATS 2025 Minimum Width for Universal Approximation using Squashable Activation Functions ICML 2025 Neural Operators for Predictor Feedback Control of Nonlinear Delay Systems L4DC 2025 Revisiting Random Walks for Learning on Graphs ICLR 2025 Batch normalization is sufficient for universal function approximation in CNNs ICLR 2024 Characterizing ResNet’s Universal Approximation Capability ICML 2024 Deep Neural Network Approximation of Invariant Functions through Dynamical Systems JMLR 2024 DE-HNN: An effective neural model for Circuit Netlist representation AISTATS 2024 Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters NeurIPS 2024 Inverse M-Kernels for Linear Universal Approximators of Non-Negative Functions NeurIPS 2024 Light Unbalanced Optimal Transport NeurIPS 2024 Meta-Learning Universal Priors Using Non-Injective Change of Variables NeurIPS 2024 Minimum width for universal approximation using ReLU networks on compact domain ICLR 2024 On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs) NeurIPS 2024 On the Intrinsic Structures of Spiking Neural Networks JMLR 2024 Rethinking 3D Convolution in ℓ_p-norm Space NeurIPS 2024