3 papers
cs.LG2026
From Benchmark Performance to Tool Deployment: Human-in-the-Loop Anomaly Detection
Mike Szklarzewski, CJ George, Gavin Smithson +10
Automated anomaly detection methods often report strong performance on curated academic benchmarks, but their behavior under real-world industrial conditions is less clear. In this…
cs.LG2026
Efficient Compression of Structured and Unstructured Volumes via Learned 3D Gaussian Representation
Landon Dyken, Sharmistha Chakrabarti, Nathan Debardeleben +4
Recent work has shown that implicit neural representations (INRs) can be trained to effectively compress structured and unstructured volume data, allowing for direct data querying…
cs.LG2026
The High Explosives and Affected Targets (HEAT) Dataset
Bryan Kaiser, Kyle Hickmann, Sharmistha Chakrabarti +6
Artificial Intelligence (AI) surrogate models provide a computationally efficient alternative to full-physics simulations, but no public datasets currently exist for training and v…