Search Results for author:
Found 6 papers, 4 papers with code
Illumination Controllable Dehazing Network based on Unsupervised Retinex Embedding
On the one hand, the dehazing task is an illposedness problem, which means that no unique solution exists.
No Place to Hide: Dual Deep Interaction Channel Network for Fake News Detection based on Data Augmentation
Different from popular methods which take full advantage of the propagation topology structure, in this paper, we propose a novel framework for fake news detection from perspectives of semantic, emotion and data enhancement, which excavates the emotional evolution patterns of news participants during the propagation process, and a dual deep interaction channel network of semantic and emotion is designed to obtain a more comprehensive and fine-grained news representation with the consideration of comments.
Fooling the Image Dehazing Models by First Order Gradient
In this paper, we focus on designing a group of attack methods based on first order gradient to verify the robustness of the existing dehazing algorithms.
Learning the Relation between Similarity Loss and Clustering Loss in Self-Supervised Learning
However, the relation between these two losses is not clear.
AlignVE: Visual Entailment Recognition Based on Alignment Relations
Such approaches, however, ignore the VE's unique nature of relation inference between the premise and hypothesis.
Bilinear Scoring Function Search for Knowledge Graph Learning
We first set up a search space for AutoBLM by analyzing existing scoring functions.
Ranked #6 on
Link Property Prediction
on ogbl-biokg
