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)

Adversarially Learned Representations for Information Obfuscation and Inference ICML 2019
A Kernel Perspective for Regularizing Deep Neural Networks ICML 2019
Adversarial Attacks on Node Embeddings via Graph Poisoning ICML 2019
Compositional Fairness Constraints for Graph Embeddings ICML 2019
Unreproducible Research is Reproducible ICML 2019
Deep Counterfactual Regret Minimization ICML 2019
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem ICML 2019
Learning Generative Models across Incomparable Spaces ICML 2019
What is the Effect of Importance Weighting in Deep Learning? ICML 2019
Learning Action Representations for Reinforcement Learning ICML 2019
Generative Adversarial User Model for Reinforcement Learning Based Recommendation System ICML 2019
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels ICML 2019
Multivariate-Information Adversarial Ensemble for Scalable Joint Distribution Matching ICML 2019
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables ICML 2019
Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning ICML 2019
Gauge Equivariant Convolutional Networks and the Icosahedral CNN ICML 2019
A fully differentiable beam search decoder ICML 2019
Shape Constraints for Set Functions ICML 2019
Flexibly Fair Representation Learning by Disentanglement ICML 2019
Approximated Oracle Filter Pruning for Destructive CNN Width Optimization ICML 2019
Width Provably Matters in Optimization for Deep Linear Neural Networks ICML 2019
Gradient Descent Finds Global Minima of Deep Neural Networks ICML 2019
Optimal Auctions through Deep Learning ICML 2019
Wasserstein of Wasserstein Loss for Learning Generative Models ICML 2019
Band-limited Training and Inference for Convolutional Neural Networks ICML 2019