Domain Generalization

RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whitening CVPR 2021 Robust Visual Reasoning via Language Guided Neural Module Networks NeurIPS 2021 S2R-DepthNet: Learning a Generalizable Depth-Specific Structural Representation CVPR 2021 SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies ICML 2021 SelfReg: Self-Supervised Contrastive Regularization for Domain Generalization ICCV 2021 Self-Supervised Adversarial Distribution Regularization for Medication Recommendation IJCAI 2021 Semantically Coherent Out-of-Distribution Detection ICCV 2021 Semantic Segmentation With Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization CVPR 2021 Shape-Biased Domain Generalization via Shock Graph Embeddings ICCV 2021 Shape-Texture Debiased Neural Network Training ICLR 2021 SIGMORPHON 2021 Shared Task on Morphological Reinflection: Generalization Across Languages ACL 2021 Size-Invariant Graph Representations for Graph Classification Extrapolations ICML 2021 SpeakerStew: Scaling to Many Languages with a Triaged Multilingual Text-Dependent and Text-Independent Speaker Verification System Interspeech 2021 Spurious Correlations in Cross-Topic Argument Mining ACL 2021 Stable Adversarial Learning under Distributional Shifts AAAI 2021 Subgraph Federated Learning with Missing Neighbor Generation NeurIPS 2021 SWAD: Domain Generalization by Seeking Flat Minima NeurIPS 2021 Systematic generalisation with group invariant predictions ICLR 2021 Taskography: Evaluating robot task planning over large 3D scene graphs CoRL 2021 Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization NeurIPS 2021 Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data ACL 2021 The OOD Blind Spot of Unsupervised Anomaly Detection MIDL 2021 Towards a Theoretical Framework of Out-of-Distribution Generalization NeurIPS 2021 Towards a Universal Model for Cross-Dataset Crowd Counting ICCV 2021 Towards Context-Agnostic Learning Using Synthetic Data NeurIPS 2021