conftrace_

Deep Learning

66,648 papers (25 classified directly here)

Subtopics

Learning Types (28,663) Architectures (27,448) Models (16,617) Techniques (8,241) Optimization & Theory (6,829) Application Areas (46)

Papers per year

2
65
428
6150
10854
'05
'10
'15
'20
'25

Papers (including subtopics)

Distributional reinforcement learning with linear function approximation AISTATS 2019
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function AISTATS 2019
Amortized Variational Inference with Graph Convolutional Networks for Gaussian Processes AISTATS 2019
Avoiding Latent Variable Collapse with Generative Skip Models AISTATS 2019
Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization AISTATS 2019
Doubly Semi-Implicit Variational Inference AISTATS 2019
Correspondence Analysis Using Neural Networks AISTATS 2019
Variance reduction properties of the reparameterization trick AISTATS 2019
Variational Noise-Contrastive Estimation AISTATS 2019
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era AISTATS 2019
Deep Topic Models for Multi-label Learning AISTATS 2019
On the Dynamics of Gradient Descent for Autoencoders AISTATS 2019
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference AISTATS 2019
Theoretical Analysis of Efficiency and Robustness of Softmax and Gap-Increasing Operators in Reinforcement Learning AISTATS 2019
A Fast Sampling Algorithm for Maximum Inner Product Search AISTATS 2019
A recurrent Markov state-space generative model for sequences AISTATS 2019
Adversarial Discrete Sequence Generation without Explicit NeuralNetworks as Discriminators AISTATS 2019
Sample-Efficient Imitation Learning via Generative Adversarial Nets AISTATS 2019
Reparameterizing Distributions on Lie Groups AISTATS 2019
Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization AISTATS 2019
The LORACs Prior for VAEs: Letting the Trees Speak for the Data AISTATS 2019
Fixing Mini-batch Sequences with Hierarchical Robust Partitioning AISTATS 2019
Representation Learning on Graphs: A Reinforcement Learning Application AISTATS 2019
Convergence of Gradient Descent on Separable Data AISTATS 2019
Structured Neural Topic Models for Reviews AISTATS 2019