1 citations · 1 across the 4 of their papers we have counts for
4 papers
Aligning Language Models with Observational Data: Opportunities and Risks from a Causal Perspective
Erfan Loghmani
Large language models are being widely used across industries to generate text that contributes directly to key performance metrics, such as medication adherence in patient messagi…
TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs
Julia Gastinger, Shenyang Huang, Mikhail Galkin +9
Multi-relational temporal graphs are powerful tools for modeling real-world data, capturing the evolving and interconnected nature of entities over time. Recently, many novel model…
Effect of Choosing Loss Function when Using T-batching for Representation Learning on Dynamic Networks
Erfan Loghmani, MohammadAmin Fazli
Representation learning methods have revolutionized machine learning on networks by converting discrete network structures into continuous domains. However, dynamic networks that e…
RPS: Portfolio Asset Selection using Graph based Representation Learning
MohammadAmin Fazli, Parsa Alian, Ali Owfi +1
Portfolio optimization is one of the essential fields of focus in finance. There has been an increasing demand for novel computational methods in this area to compute portfolios wi…