research
∙
07/24/2023
LLM-Rec: Personalized Recommendation via Prompting Large Language Models
We investigate various prompting strategies for enhancing personalized r...
share
research
∙
06/20/2023
CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems
Multi-agent dynamical systems refer to scenarios where multiple units in...
research
∙
12/11/2022
A model-data asymptotic-preserving neural network method based on micro-macro decomposition for gray radiative transfer equations
We propose a model-data asymptotic-preserving neural network(MD-APNN) me...
research
∙
10/20/2022
Tele-Knowledge Pre-training for Fault Analysis
In this work, we share our experience on tele-knowledge pre-training for...
research
∙
10/16/2022
Learning Probabilities of Causation from Finite Population Data
This paper deals with the problem of learning the probabilities of causa...
research
∙
10/15/2022
Unit Selection: Learning Benefit Function from Finite Population Data
The unit selection problem is to identify a group of individuals who are...
research
∙
10/08/2022
Relational Message Passing for Fully Inductive Knowledge Graph Completion
In knowledge graph completion (KGC), predicting triples involving emergi...
research
∙
10/09/2021
Deep Learning of Potential Outcomes
This review systematizes the emerging literature for causal inference us...
research
∙
11/17/2019
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks
Graph convolutional networks (GCNs) have recently received wide attentio...
research
∙
05/06/2018
