19 citations · 35 across the 7 of their papers we have counts for
7 papers
BLADE: Benchmarking Language Model Agents for Data-Driven Science
Ken Gu, Ruoxi Shang, Ruien Jiang +13
Data-driven scientific discovery requires the iterative integration of scientific domain knowledge, statistical expertise, and an understanding of data semantics to make nuanced an…
How Do Analysts Understand and Verify AI-Assisted Data Analyses?
Ken Gu, Ruoxi Shang, Tim Althoff +2
Data analysis is challenging as it requires synthesizing domain knowledge, statistical expertise, and programming skills. Assistants powered by large language models (LLMs), such a…
How Do Data Analysts Respond to AI Assistance? A Wizard-of-Oz Study
Ken Gu, Madeleine Grunde-McLaughlin, Andrew M. McNutt +2
Data analysis is challenging as analysts must navigate nuanced decisions that may yield divergent conclusions. AI assistants have the potential to support analysts in planning thei…
Understanding and Supporting Debugging Workflows in Multiverse Analysis
Ken Gu, Eunice Jun, Tim Althoff
Multiverse analysis, a paradigm for statistical analysis that considers all combinations of reasonable analysis choices in parallel, promises to improve transparency and reproducib…
Bi-Level Graph Neural Networks for Drug-Drug Interaction Prediction
Yunsheng Bai, Ken Gu, Yizhou Sun +1
We introduce Bi-GNN for modeling biological link prediction tasks such as drug-drug interaction (DDI) and protein-protein interaction (PPI). Taking drug-drug interaction as an exam…
Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity
Yunsheng Bai, Hao Ding, Yang Qiao +5
We introduce a novel approach to graph-level representation learning, which is to embed an entire graph into a vector space where the embeddings of two graphs preserve their graph-…
Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching
Yunsheng Bai, Hao Ding, Yizhou Sun +1
Graph similarity computation is one of the core operations in many graph-based applications, such as graph similarity search, graph database analysis, graph clustering, etc. Since…