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Architectures

27,448 papers (33 classified directly here)

Subtopics

Neural Networks (11,723) Transformers (10,397) Graph Neural Networks (4,522) Autoencoders (1,154) Convolutional Neural Networks (973) Recurrent Neural Networks (593) Generative Adversarial Networks (18) Encoder-Decoder (14)

Papers per year

27
213
2915
3174
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'25

Papers (including subtopics)

Enhancing Graph Representation Learning with Localized Topological Features JMLR 2025
Random ReLU Neural Networks as Non-Gaussian Processes JMLR 2025
Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick JMLR 2025
Orthogonal Bases for Equivariant Graph Learning with Provable k-WL Expressive Power JMLR 2025
Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning JMLR 2025
Local Linear Recovery Guarantee of Deep Neural Networks at Overparameterization JMLR 2025
Derivative-Informed Neural Operator Acceleration of Geometric MCMC for Infinite-Dimensional Bayesian Inverse Problems JMLR 2025
GraphNeuralNetworks.jl: Deep Learning on Graphs with Julia JMLR 2025
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification JMLR 2025
Implicit vs Unfolded Graph Neural Networks JMLR 2025
Feature Learning in Finite-Width Bayesian Deep Linear Networks with Multiple Outputs and Convolutional Layers JMLR 2025
Learning conditional distributions on continuous spaces JMLR 2025
DRM Revisited: A Complete Error Analysis JMLR 2025
BitNet: 1-bit Pre-training for Large Language Models JMLR 2025
Transformers from Diffusion: A Unified Framework for Neural Message Passing JMLR 2025
On the O(sqrt(d)/T^(1/4)) Convergence Rate of RMSProp and Its Momentum Extension Measured by l_1 Norm JMLR 2025
Minimax Optimal Deep Neural Network Classifiers Under Smooth Decision Boundary JMLR 2025
On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory JMLR 2025
On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes JMLR 2025
Autoencoders in Function Space JMLR 2025
Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods JMLR 2025
Interpretable Global Minima of Deep ReLU Neural Networks on Sequentially Separable Data JMLR 2025
High-Rank Irreducible Cartesian Tensor Decomposition and Bases of Equivariant Spaces JMLR 2025
Multiple Instance Verification JMLR 2025
Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation JMLR 2025