- 17.06 - Self-Normalizing Neural Networks
- 17.06 - StreetStyle: Exploring world-wide clothing styles from millions of photos
- 17.05 - Visual Attribute Transfer through Deep Image Analogy
- 17.05 - pix2code: Generating Code from a Graphical User Interface Screenshot
- 17.05 - A System for Accessible Artificial Intelligence
- 17.05 - Domain Adaptation with Randomized Multilinear Adversarial Networks
- 17.04 - Softmax GAN
- 17.04 - Generate To Adapt - Aligning Domains using Generative Adversarial Networks
- 17.03 - Neural Episodic Control
- 17.03 - Mask R-CNN
- 17.03 - BEGAN- Boundary Equilibrium Generative Adversarial Networks
- 17.03 - Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
- 17.02 - Understanding Deep Learning Requires Rethinking Generalization
- 17.02 - Adversarial Discriminative Domain Adaptation
- 17.01 - Cost-Effective Active Learning for Deep Image Classification
- 17.01 - Wasserstein GAN
- 17.01 - NIPS Tutorial - Generative Adversarial Networks
- 17.01 - Learning From Noisy Large-Scale Datasets With Minimal Supervision
- 16.12 - Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space
- 16.12 - YOLO9000: Better, Faster, Stronger
- 16.11 - Deep Information Propagation
- 16.11 - Speed/accuracy trade-offs for modern convolutional object detectors
- 16/11 - Neural Architecture Search with Reinforcement Learning
- 16.07 - Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation
- 16.05 - Domain-Adversarial Training of Neural Networks
- 16.01 - Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- 15.12 - Deep Residual Learning for Image Recognition
- 15.11 - Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
- 15.04 - Active Learning by Learning
- 15.04 - Fast R-CNN
- 15.02 - Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 14.12 - Dropout: A Simple Way to Prevent Neural Networks from Overfitting
- 14.12 - Training Deep Neural Networks on Noisy Labels with Bootstrapping
- 14.11 - Conditional Generative Adversarial Nets
- 14.09 - Unsupervised Domain Adaptation by Backpropagation
- 14.06 - Generative Adversarial Nets
- 14.06 - Learning and Transferring Mid-Level Image Representations using Convolutional Neural Networks
- 11.06 - Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction
- 10.06 - Deconvolutional Networks
- 10.01 - Active Learning Literature Survey