43 citations · 46 across the 5 of their papers we have counts for
6 papers
Nexus: Inferring Join Graphs from Metadata Alone via Iterative Low-Rank Matrix Completion
Tianji Cong, Yuanyuan Tian, Andreas Mueller +5
Automatically inferring join relationships is a critical task for effective data discovery, integration, querying and reuse. However, accurately and efficiently identifying these r…
Optimizing open-domain question answering with graph-based retrieval augmented generation
Joyce Cahoon, Prerna Singh, Nick Litombe +6
In this work, we benchmark various graph-based retrieval-augmented generation (RAG) systems across a broad spectrum of query types, including OLTP-style (fact-based) and OLAP-style…
Open Challenges in Time Series Anomaly Detection: An Industry Perspective
Andreas Mueller
Current research in time-series anomaly detection is using definitions that miss critical aspects of how anomaly detection is commonly used in practice. We list several areas that…
GAMformer: Bridging Tabular Foundation Models and Interpretable Machine Learning
Andreas Mueller, Julien Siems, Harsha Nori +4
While interpretability is crucial for machine learning applications in safety-critical domains and for regulatory compliance, existing tabular foundation models like TabPFN lack tr…
Wireless 6G Connectivity for Massive Number of Devices and Critical Services
Anders E. Kalør, Giuseppe Durisi, Sinem Coleri +4
Compared to the generations up to 4G, whose main focus was on broadband and coverage aspects, 5G has expanded the scope of wireless cellular systems towards embracing two new types…
MotherNet: Fast Training and Inference via Hyper-Network Transformers
Andreas Müller, Carlo Curino, Raghu Ramakrishnan
Foundation models are transforming machine learning across many modalities, with in-context learning replacing classical model training. Recent work on tabular data hints at a simi…