5 papers
CausalPre: Scalable and Effective Data Pre-Processing for Causal Fairness
Ying Zheng, Yangfan Jiang, Kian-Lee Tan
Causal fairness in databases is crucial to preventing biased and inaccurate outcomes in downstream tasks. While most prior work assumes a known causal model, recent efforts relax t…
Mixture-of-Experts Operator Transformer for Large-Scale PDE Pre-Training
Hong Wang, Haiyang Xin, Jie Wang +4
Pre-training has proven effective in addressing data scarcity and performance limitations in solving PDE problems with neural operators. However, challenges remain due to the heter…
The Denario project: Deep knowledge AI agents for scientific discovery
Francisco Villaescusa-Navarro, Boris Bolliet, Pablo Villanueva-Domingo +33
We present Denario, an AI multi-agent system designed to serve as a scientific research assistant. Denario can perform many different tasks, such as generating ideas, checking the…
Predictive Response Optimization: Using Reinforcement Learning to Fight Online Social Network Abuse
Garrett Wilson, Geoffrey Goh, Yan Jiang +4
Detecting phishing, spam, fake accounts, data scraping, and other malicious activity in online social networks (OSNs) is a problem that has been studied for well over a decade, wit…
The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning
Ruben Ohana, Michael McCabe, Lucas Meyer +24
Machine learning based surrogate models offer researchers powerful tools for accelerating simulation-based workflows. However, as standard datasets in this space often cover small…