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Battling the Non-stationarity in Time Series Forecasting via Test-time Adaptation

AAAI Conference on Artificial Intelligence

Disentangled Motion Modeling for Video Frame Interpolation

Computer Vision and Pattern Recognition Conference (CVPR)

TAROT: Towards Essentially Domain-Invariant Robustness with Theoretical Justification

Journal of the Korean Statistical Society

Meta-ANOVA: Screening Interactions for Interpretable Machine Learning

International Conference on Machine Learning (ICML)

Fair Clustering via Alignment

Journal of Law & Innovation

Measuring Regulatory Overlap Between Horizontal AI Law and Sectoral Regulations: A Case Study on “High-Risk” AI Systems in Annex I of the EU AI Act

IEEE Transactions on Pattern Analysis And Machine Intelligence

Fair Representation Learning for Continuous Sensitive Attributes Using Expectation of Integral Probability Metrics

Scientific Data

1.5 million materials narratives generated by chatbots

International Conference on Learning Representations

Entropy is not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors

International Conference on Learning Representations

DAFA: Distance-Aware Fair Adversarial Training

International Conference on Learning Representations (ICLR)

SF(DA)2: Source-free Domain Adaptation Through the Lens of Data Augmentation

ACM International Conference on Information and Knowledge Management

CKNN: Cleansed k-Nearest Neighbor for Unsupervised Video Anomaly Detection

ControlDreamer: Stylized 3D Generation with Multi-View ControlNet

Neural Information Processing Systems (NeurIPS)

Paralinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation

Neural Information Processing Systems (NeurIPS)

Textual Training for the Hassle-Free Removal of Unwanted Visual Data : Case Studies on OOD and Hateful Image Detection

Neural Information Processing Systems (NeurIPS)

Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting

Transactions on Machine Learning Research

Fairness Through Matching

IEEE/CVF International Conference on Computer Vision (ICCV)

Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge Distillation

International Conference on Machine Learning (ICML)

Covariate Balancing Using the Integral Probability Metric for Causal Inference

International Conference on Machine Learning (ICML)

On the Impact of Knowledge Distillation for Model Interpretability

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