7 citations · 10 across the 14 of their papers we have counts for
5 papers · 1 filter
Recall and Refine: A Simple but Effective Source-free Open-set Domain Adaptation Framework
Ismail Nejjar, Hao Dong, Olga Fink
Open-set Domain Adaptation (OSDA) aims to adapt a model from a labeled source domain to an unlabeled target domain, where novel classes - also referred to as target-private unknown…
Towards Multimodal Open-Set Domain Generalization and Adaptation through Self-supervision
Hao Dong, Eleni Chatzi, Olga Fink
The task of open-set domain generalization (OSDG) involves recognizing novel classes within unseen domains, which becomes more challenging with multiple modalities as input. Existi…
Unseen Visual Anomaly Generation
Han Sun, Yunkang Cao, Hao Dong +1
Visual anomaly detection (AD) presents significant challenges due to the scarcity of anomalous data samples. While numerous works have been proposed to synthesize anomalous samples…
MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities
Hao Dong, Yue Zhao, Eleni Chatzi +1
Detecting out-of-distribution (OOD) samples is important for deploying machine learning models in safety-critical applications such as autonomous driving and robot-assisted surgery…
Interactive Symbolic Regression through Offline Reinforcement Learning: A Co-Design Framework
Yuan Tian, Wenqi Zhou, Michele Viscione +3
Symbolic Regression (SR) holds great potential for uncovering underlying mathematical and physical relationships from observed data. However, the vast combinatorial space of possib…