conftrace_

approximation theory

77 papers

Explore in graph

Co-occurring keywords

neural network (6616) relu network (143) function approximation (319) activation function (133) neural network approximation (31) kernel methods (1097) graph neural network (3962) partial differential equation (222) curse of dimensionality (61) neural network optimization (1293)

Papers

Composable Coresets for Determinant Maximization: Greedy is Almost Optimal NIPS 2023
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem NIPS 2023
Limitations on approximation by deep and shallow neural networks JMLR 2023
KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-zero Training Loss AAAI 2022
Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers NIPS 2022
Approximation with CNNs in Sobolev Space: with Applications to Classification NIPS 2022
Learning with convolution and pooling operations in kernel methods NIPS 2022
Efficient learning of sparse and decomposable PDEs using random projection UAI 2022
Deep Network Approximation in Terms of Intrinsic Parameters ICML 2022
A spectral-based analysis of the separation between two-layer neural networks and linear methods JMLR 2022
Depth separation beyond radial functions JMLR 2022
On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds NIPS 2022
A Theoretical View on Sparsely Activated Networks NIPS 2022
A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks NIPS 2022
Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks JMLR 2022
Theoretically Provable Spiking Neural Networks NIPS 2022
Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited NIPS 2022
Expressivity of Neural Networks via Chaotic Itineraries beyond Sharkovsky’s Theorem AISTATS 2022
Neural Network Architecture Beyond Width and Depth NIPS 2022
Size and depth of monotone neural networks: interpolation and approximation NIPS 2022
Coin Flipping Neural Networks ICML 2022
On the Universality of Graph Neural Networks on Large Random Graphs NIPS 2021
Efficient Interpolation of Density Estimators AISTATS 2021
Approximation Theory of Convolutional Architectures for Time Series Modelling ICML 2021
PSD Representations for Effective Probability Models NIPS 2021