conftrace_

distribution shift

722 papers

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Also known as

DS

Co-occurring keywords

domain adaptation (4595) domain generalization (1522) out-of-distribution detection (617) test-time adaptation (312) out-of-distribution generalization (408) causal inference (1630) representation learning (6206) transfer learning (5449) covariate shift (157) graph neural network (3962)

Papers

On $f$-Divergence Principled Domain Adaptation: An Improved Framework NIPS 2024
OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning NIPS 2024
Any-Shift Prompting for Generalization over Distributions CVPR 2024
Distribution Shifts Are Bottlenecks: Extensive Evaluation for Grounding Language Models to Knowledge Bases EACL 2024
Causal Temporal Representation Learning with Nonstationary Sparse Transition NIPS 2024
Domain Gap Embeddings for Generative Dataset Augmentation CVPR 2024
CaDeT: a Causal Disentanglement Approach for Robust Trajectory Prediction in Autonomous Driving CVPR 2024
Conformalized Semi-supervised Random Forest for Classification and Abnormality Detection AISTATS 2024
Continual-MAE: Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation CVPR 2024
Efficient Test-Time Adaptation of Vision-Language Models CVPR 2024
How safe am I given what I see? Calibrated prediction of safety chances for image-controlled autonomy L4DC 2024
PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees CVPR 2024
REDUCR: Robust Data Downsampling using Class Priority Reweighting NIPS 2024
Your Transferability Barrier is Fragile: Free-Lunch for Transferring the Non-Transferable Learning CVPR 2024
DEM: Distribution Edited Model for Training with Mixed Data Distributions EMNLP 2024
Enhancing Zero-Shot Vision Models by Label-Free Prompt Distribution Learning and Bias Correcting NIPS 2024
Multimodal Graph Neural Architecture Search under Distribution Shifts AAAI 2024
Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment NIPS 2024
Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior AAAI 2024
Self-Healing Machine Learning: A Framework for Autonomous Adaptation in Real-World Environments NIPS 2024
MaNo: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts NIPS 2024
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts NIPS 2024
Robust Weight Signatures: Gaining Robustness as Easy as Patching Weights? ICML 2023
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness NIPS 2023
Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts NIPS 2023