Representation Learning

Improving Entity Linking through Semantic Reinforced Entity Embeddings ACL 2020 Improving the Robustness of Capsule Networks to Image Affine Transformations CVPR 2020 Improving Transformer Models by Reordering their Sublayers ACL 2020 Incorporating Interpretable Output Constraints in Bayesian Neural Networks NeurIPS 2020 Incremental Sense Weight Training for In-Depth Interpretation of Contextualized Word Embeddings (Student Abstract) AAAI 2020 Incremental Text-to-Speech Synthesis with Prefix-to-Prefix Framework EMNLP 2020 Independence Promoted Graph Disentangled Networks AAAI 2020 Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations AISTATS 2020 InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs ICML 2020 Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip AAAI 2020 Information-Theoretic Probing with Minimum Description Length EMNLP 2020 Informative Dropout for Robust Representation Learning: A Shape-bias Perspective ICML 2020 In search of isoglosses: continuous and discrete language embeddings in Slavic historical phonology ACL 2020 INSET: Sentence Infilling with INter-SEntential Transformer ACL 2020 Instance-Adaptive Graph for EEG Emotion Recognition AAAI 2020 Instance-wise Feature Grouping NeurIPS 2020 Integrating Deep Learning with Logic Fusion for Information Extraction AAAI 2020 Integrating Relation Constraints with Neural Relation Extractors AAAI 2020 Interpretable Entity Representations through Large-Scale Typing EMNLP 2020 Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings ACL 2020 Intra- and Inter-Action Understanding via Temporal Action Parsing CVPR 2020 Intrinsic Probing through Dimension Selection EMNLP 2020 Introducing Syntactic Structures into Target Opinion Word Extraction with Deep Learning EMNLP 2020 Invariant Representations through Adversarial Forgetting AAAI 2020 Inverse Learning of Symmetries NeurIPS 2020