4 accepted papers
Multi-modal learning approaches that integrate pathological images with genomic profiles have significantly enhanced the accuracy of survival prediction tasks. However, previous methods often struggle to effectively process long-range gigapixel whole slide images (WSIs) and sparse genomic profiles d
Unsupervised Domain Adaptation (UDA) is essential for deploying medical segmentation models across diverse clinical environments. Existing methods are fundamentally limited, suffering from semantically unaware feature alignment that results in poor distributional fidelity and from pseudo-label valid
Learning is crucial for automated negotiation, and recent years have witnessed a remarkable achievement in application of reinforcement learning (RL) for various negotiation tasks. Conventional RL methods focus generally on learning from active interactions with opposing negotiators. However, collec…
Arbitrary-scale image super-resolution (SR) is often tackled using the implicit neural representation (INR) approach, which relies on a position encoding scheme to improve its representation ability. In this paper, we introduce orthogonal position encoding (OPE), an extension of position encoding, a…