Search Results for author:
Found 6 papers, 4 papers with code
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
The rapid development of open-source large language models (LLMs) has been truly remarkable.
Audience Expansion for Multi-show Release Based on an Edge-prompted Heterogeneous Graph Network
In the offline stage, to construct the graph, user IDs and specific side information combinations of the shows are chosen to be the nodes, and click/co-click relations and view time are used to build the edges.
RA V-Net: Deep learning network for automated liver segmentation
CA Module (Channel Attention Module) is introduced, which used to extract relevant channels with dependencies and strengthen them by matrix dot product, while weakening irrelevant channels without dependencies.
Component Divide-and-Conquer for Real-World Image Super-Resolution
Learning an SR model with conventional pixel-wise loss usually is easily dominated by flat regions and edges, and fails to infer realistic details of complex textures.
Difficulty-aware Image Super Resolution via Deep Adaptive Dual-Network
To identify whether a region is easy or hard, we propose a novel image difficulty recognition network based on PSNR prior.
Predicting protein inter-residue contacts using composite likelihood maximization and deep learning
We further present successful application of the predicted contacts to accurately build tertiary structures for proteins in the PSICOV dataset.
