- Meta Reinforcement Learning as Task Inference
- Character Region Awareness for Text Detection
- Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables
- Bi-Directional Cascade Network for Perceptual Edge Detection
- Fast Interactive Object Annotation with Curve-GCN
- Do NLP Models Know Numbers? Probing Numeracy in Embeddings
- Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
- Feature Denoising for Improving Adversarial Robustness
- Factorization Machine
- Solving the Defect in Application of Compact Abating Probability to Convolutional Neural Network Based Open Set Recognition
- Auto-Encoding Variational Bayes
- Are Noisy Sentences Useless for Distant Supervised Relation Extraction?
- Sequential Decision Making Problems
- StarGAN v2: Diverse Image Synthesis for Multiple Domains
- DeepLab Series
- Causal Confusion in Imitation Learning
- Unsupervised Person Re-identification by Soft Multilabel Learning
- Adversarial Examples Are Not Bugs, They Are Features
- Discriminator Rejection Sampling
- Super-Resolving Very Low-Resolution Face Images with Supplementary Attributes
- Detection and Analysis of Self-Disclosure in Online News Commentaries
- Session-based Recommendations with Recurrent Neural Networks
- A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
- Bidirectional Attention Flow for Machine Comprehension
- Momentum Contrast for Unsupervised Visual Representation Learning
- MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation
- Meta-learning: Learning-to-Learn in Neural Networks
- Deep Transfer Learning for Multiple Class Novelty Detection
- Slowing Down the Weight Norm Increase in Momentum-based Optimizers
- Joint Modelling of Emotion and Abusive Language Detection
- Exploration Strategies in Reinforcement Learning
- Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network
- Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
- Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning