Advanced domain adaptation techniques for robust machine learning across different data distributions

Code for "Improving Stain Invariance of CNNs for Segmentation by Fusing Channel Attention and Domain-Adversarial Training"

Implementation of paper: Equivariant Learning for Out-of-Distribution Cold-start Recommendation. (backbone model CLCRec) (MM'23)

Official implementation of NeurIPS 2025 paper "Visual Instruction Bottleneck Tuning"

Coping with Label Shift via Distributionally Robust Optimisation

Code for "LLM Embeddings Improve Test-time Adaptation to Tabular Y|X-Shifts"

"RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning" by Yue Duan (ECCV 2022)

Robust and Highly Sensitive Covariate Shift Detection using XGBoost

Code for the Conditional Mutual Information-Debiasing (CMID) method.

Code for the paper "Where are we with calibration under dataset shift in image classification?"

[ICLR 2023] Official Tensorflow implementation of "Distributionally Robust Post-hoc Classifiers under Prior Shifts"

Quilt: Robust Data Segment Selection against Concept Drifts (AAAI 2024)

[TMLR 2025] Importance Weighting for Aligning Language Models under Deployment Distribution Shift

Code for the control+shift paper, where a method for generating general datasets with a controllable amount of distribution shift was proposed. Presented at the ECCV'24 "Synthetic Data for Computer Vision" workshop.

[NeurIPS 2023 (Spotlight)] Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts

Code accompanying our paper titled Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms

[WWW2024 (Oral)] PyTorch implementation of "Intelligent Model Update Strategy for Sequential Recommendation".