12 papers
Agentic Root Cause Analysis through Evidence-Grounded Reasoning
Amaury Wei, Olga Fink
Diagnosing the root cause of anomalies is essential for safe industrial operation. Despite extensive sensor instrumentation, formulating hypotheses and gathering evidence remains a…
Neural Kolmogorov Equations: Parallelizable Learning of Stochastic Dynamics under General Noise
Arthur Bizzi, Olga Fink
Neural stochastic differential equations (SDEs) have emerged as powerful tools for learning noisy or stochastic dynamics directly from data; however, existing approaches largely as…
Beyond Thermal Imaging: Inferring Thermophysical Properties from Time-Resolved Thermal Observations
Chenghao Xu, Malcolm Mielle, Olga Fink
Inferring latent physical properties from sensory observations is a fundamental challenge in machine perception. Among available sensing modalities, thermal imaging is particularly…
Relational and Sequential Conformal Inference for Energy Time Series over Graphs via Foundation Models
Keivan Faghih Niresi, Alice Cicirello, Olga Fink
Accurate energy demand forecasting is essential for the reliable operation and planning of modern sustainable energy systems. Spatial-temporal graph neural networks (STGNNs) have r…
Rethinking Object-Centric Representations for Video Dynamics Modeling
Amaury Wei, Ismail Nejjar, Olga Fink
Unsupervised video object tracking aims to decompose dynamic scenes into persistent, object-centric entities without manual annotations. Many recent approaches rely on slot-based r…
Graph Signal Separation with Learnable Spectral Filters
Keivan Faghih Niresi, Dorina Thanou, Olga Fink
Separating multiple graph signals from a single observed mixture is an inherently ill-posed problem that traditionally relies on restrictive and handcrafted priors. This letter add…