conftrace_
← Deep Learning
Deep Learning ›

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
'10
'15
'20
'25

Papers (including subtopics)

Surface Reconstruction based on Self-Merging Octree with Deep Learning ACML 2019
Fusing Recalibrated Features and Depthwise Separable Convolution for the Mangrove Bird Sound Classification ACML 2019
Multi-Scale Visual Semantics Aggregation with Self-Attention for End-to-End Image-Text Matching ACML 2019
Improving Relation Classification by Entity Pair Graph ACML 2019
Towards a Theoretical Understanding of Hashing-Based Neural Nets AISTATS 2019
Unbiased Implicit Variational Inference AISTATS 2019
KAMA-NNs: Low-dimensional Rotation Based Neural Networks AISTATS 2019
Graph Embedding with Shifted Inner Product Similarity and Its Improved Approximation Capability AISTATS 2019
Robust Graph Embedding with Noisy Link Weights AISTATS 2019
Bayesian Learning of Neural Network Architectures AISTATS 2019
Deep Neural Networks Learn Non-Smooth Functions Effectively AISTATS 2019
Fisher-Rao Metric, Geometry, and Complexity of Neural Networks AISTATS 2019
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach AISTATS 2019
On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition AISTATS 2019
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent AISTATS 2019
Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex AISTATS 2019
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron AISTATS 2019
Adaptive Ensemble Prediction for Deep Neural Networks based on Confidence Level AISTATS 2019
Classifying Signals on Irregular Domains via Convolutional Cluster Pooling AISTATS 2019
Training a Spiking Neural Network with Equilibrium Propagation AISTATS 2019
Learning One-hidden-layer ReLU Networks via Gradient Descent AISTATS 2019
Calibrating Deep Convolutional Gaussian Processes AISTATS 2019
Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning AISTATS 2019
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning AISTATS 2019
Probabilistic Forecasting with Spline Quantile Function RNNs AISTATS 2019