representation learning

Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing CVPR 2021 Directed Graph Contrastive Learning NeurIPS 2021 Directed Graph Embeddings in Pseudo-Riemannian Manifolds ICML 2021 Direction is what you need: Improving Word Embedding Compression in Large Language Models ACL 2021 DirectProbe: Studying Representations without Classifiers NAACL 2021 Discovering Representation Sprachbund For Multilingual Pre-Training EMNLP 2021 Discrete Cosine Transform as Universal Sentence Encoder ACL 2021 Discrimination-Aware Mechanism for Fine-Grained Representation Learning CVPR 2021 Disentangled Recurrent Wasserstein Autoencoder ICLR 2021 Disentangled Representation Learning in Heterogeneous Information Network for Large-scale Android Malware Detection in the COVID-19 Era and Beyond AAAI 2021 Disentangling Generative Factors in Natural Language with Discrete Variational Autoencoders EMNLP 2021 Disentangling Representations of Text by Masking Transformers EMNLP 2021 Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces ICML 2021 Disentangling Semantics and Syntax in Sentence Embeddings with Pre-trained Language Models NAACL 2021 Disentangling syntax and semantics in the brain with deep networks ICML 2021 Dissecting Image Crops ICCV 2021 Distilling Audio-Visual Knowledge by Compositional Contrastive Learning CVPR 2021 Distilling Linguistic Context for Language Model Compression EMNLP 2021 Distilling Localization for Self-Supervised Representation Learning AAAI 2021 Distilling Robust and Non-Robust Features in Adversarial Examples by Information Bottleneck NeurIPS 2021 Distilling Virtual Examples for Long-Tailed Recognition ICCV 2021 Distinct Label Representations for Few-Shot Text Classification ACL 2021 Distributed Representations of Emotion Categories in Emotion Space ACL 2021 Distributional Robustness Loss for Long-Tail Learning ICCV 2021 Divide and Contrast: Self-Supervised Learning From Uncurated Data ICCV 2021