Zobrazeno 1 - 10
of 172
pro vyhledávání: '"Zhang, Zecheng"'
Single-operator learning involves training a deep neural network to learn a specific operator, whereas recent work in multi-operator learning uses an operator embedding structure to train a single neural network on data from multiple operators. Thus,
Externí odkaz:
http://arxiv.org/abs/2408.16168
Autor:
Zhang, Zecheng
Grid startup, an integral component of the power system, holds strategic importance for ensuring the reliability and efficiency of the electrical grid. However, current methodologies for in-depth analysis and precise prediction of grid startup scenar
Externí odkaz:
http://arxiv.org/abs/2408.12129
Visual Question Answering (VQA) is a challenging task that requires systems to provide accurate answers to questions based on image content. Current VQA models struggle with complex questions due to limitations in capturing and integrating multimodal
Externí odkaz:
http://arxiv.org/abs/2408.07303
Autor:
Robinson, Joshua, Ranjan, Rishabh, Hu, Weihua, Huang, Kexin, Han, Jiaqi, Dobles, Alejandro, Fey, Matthias, Lenssen, Jan E., Yuan, Yiwen, Zhang, Zecheng, He, Xinwei, Leskovec, Jure
We present RelBench, a public benchmark for solving predictive tasks over relational databases with graph neural networks. RelBench provides databases and tasks spanning diverse domains and scales, and is intended to be a foundational infrastructure
Externí odkaz:
http://arxiv.org/abs/2407.20060
Autor:
Xu, Tianqi, Chen, Linyao, Wu, Dai-Jie, Chen, Yanjun, Zhang, Zecheng, Yao, Xiang, Xie, Zhiqiang, Chen, Yongchao, Liu, Shilong, Qian, Bochen, Torr, Philip, Ghanem, Bernard, Li, Guohao
The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones. Existing benchmarks for MLM age
Externí odkaz:
http://arxiv.org/abs/2407.01511
Image anomaly detection is a popular research direction, with many methods emerging in recent years due to rapid advancements in computing. The use of artificial intelligence for image anomaly detection has been widely studied. By analyzing images of
Externí odkaz:
http://arxiv.org/abs/2406.13987
This research delves deeply into Meta Reinforcement Learning (Meta RL) through a exploration focusing on defining generalization limits and ensuring convergence. By employing a approach this article introduces an innovative theoretical framework to m
Externí odkaz:
http://arxiv.org/abs/2405.13290
Autor:
Peng, Xirui, Xu, Qiming, Feng, Zheng, Zhao, Haopeng, Tan, Lianghao, Zhou, Yan, Zhang, Zecheng, Gong, Chenwei, Zheng, Yingqiao
This paper explores an automatic news generation and fact-checking system based on language processing, aimed at enhancing the efficiency and quality of news production while ensuring the authenticity and reliability of the news content. With the rap
Externí odkaz:
http://arxiv.org/abs/2405.10492
Foundation models, such as large language models, have demonstrated success in addressing various language and image processing tasks. In this work, we introduce a multi-modal foundation model for scientific problems, named PROSE-PDE. Our model, desi
Externí odkaz:
http://arxiv.org/abs/2404.12355
Autor:
Zhang, Zecheng
The study of operator learning involves the utilization of neural networks to approximate operators. Traditionally, the focus has been on single-operator learning (SOL). However, recent advances have rapidly expanded this to include the approximation
Externí odkaz:
http://arxiv.org/abs/2404.02892