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Out-of-Distribution Generalization

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TitleStatusHype
Segmentation Consistency Training: Out-of-Distribution Generalization for Medical Image SegmentationCode0
PAC Generalization via Invariant Representations—0
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor EmbeddingCode0
Comparison of Deep Learning Segmentation and Multigrader-annotated Mandibular Canals of Multicenter CBCT scans—0
Reassessing Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization—0
Memory-enriched computation and learning in spiking neural networks through Hebbian plasticityCode0
The developmental trajectory of object recognition robustness: children are like small adults but unlike big deep neural networksCode0
Diverse Weight Averaging for Out-of-Distribution GeneralizationCode1
SeqZero: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot ModelsCode0
Knowledge Graph Question Answering Datasets and Their Generalizability: Are They Enough for Future Research?Code1
Wavelet-Based Hybrid Machine Learning Model for Out-of-distribution Internet Traffic Prediction—0
Causal Transportability for Visual RecognitionCode1
Causal Reasoning Meets Visual Representation Learning: A Prospective Study—0
VITA: A Multi-Source Vicinal Transfer Augmentation Method for Out-of-Distribution Generalization—0
Out-of-distribution generalization for learning quantum dynamics—0
What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic EnvironmentCode0
Last Layer Re-Training is Sufficient for Robustness to Spurious CorrelationsCode1
Knowledge-Spreader: Learning Facial Action Unit Dynamics with Extremely Limited Labels—0
Example-based Hypernetworks for Out-of-Distribution GeneralizationCode0
Compound Domain Generalization via Meta-Knowledge Encoding—0
Out-of-distribution Generalization with Causal Invariant Transformations—0
WOODS: Benchmarks for Out-of-Distribution Generalization in Time SeriesCode1
Vision-Based Manipulators Need to Also See from Their Hands—0
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference timeCode2
Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution GeneralizationCode1
Is Neuro-Symbolic AI Meeting its Promise in Natural Language Processing? A Structured ReviewCode1
Out-Of-Distribution Generalization on Graphs: A SurveyCode1
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision—0
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution GeneralizationCode1
Learning Causally Invariant Representations for Out-of-Distribution Generalization on GraphsCode2
Generative multitask learning mitigates target-causing confoundingCode0
Uncertainty Modeling for Out-of-Distribution GeneralizationCode1
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning—0
Gradient Masked Averaging for Federated Learning—0
Revisiting Weakly Supervised Pre-Training of Visual Perception ModelsCode1
SEQZERO: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models—0
Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction ModelsCode0
OOD-GNN: Out-of-Distribution Generalized Graph Neural Network—0
An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers—0
Overparameterization Improves Robustness to Covariate Shift in High Dimensions—0
Towards Robust and Adaptive Motion Forecasting: A Causal Representation PerspectiveCode1
Composing Partial Differential Equations with Physics-Aware Neural Networks—0
Deformation Robust Roto-Scale-Translation Equivariant CNNs—0
Covariate Shift in High-Dimensional Random Feature Regression—0
Masked Autoencoders Are Scalable Vision LearnersCode1
Assessing the Generalization Capacity of Pre-trained Language Models through Japanese Adversarial Natural Language InferenceCode1
Simple data balancing achieves competitive worst-group-accuracyCode1
SCHA-VAE: Hierarchical Context Aggregation for Few-Shot GenerationCode1
Learning Representations that Support Robust Transfer of PredictorsCode1
Towards Robust Waveform-Based Acoustic Models—0
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