Publications

Design and implementation of machine learning-based anomaly detection in the ITER Tokamak Systems Monitor
The Tokamak Systems Monitor (TSM) is a software suite under development at ITER that provides operators with an integrated view of the …
Joris Paret, Brian Sammuli, Víctor Costa Pérez, Nathaniel Saura, Laura Hernández Cubo, Daniel Iglesias
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Machine Learning-Based Anomaly Detection for ITER's Tokamak Systems Monitor: A Gyrotron Case Study
The ITER Tokamak Systems Monitor will provide operators with timely assessments of machine health, component lifetime, and early …
Joris Paret, Daniel Iglesias, Daniel Sabio Ruiz, Dilin Meloni, Andrea Antonione, Ruggero Bertazzoni, Giuseppe Carannante, Martino Ferrari, María Ortiz de Zúñiga, Mario Cavinato, Francisco Sánchez Arcos, Alfredo Portone
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Preliminary machine learning-based calibration strategy for the ITER Tokamak Systems Monitor
A machine learning-based calibration strategy for the ITER Tokamak Systems Monitor (TSM) is presented, focusing on the optimization of …
Joris Paret, Daniel Iglesias, Hyogeon Bak, Matthew Clough, George Vayakis, Michael Walsh
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Dimensionality reduction of local structure in glassy binary mixtures
We consider unsupervised learning methods for characterizing the disordered microscopic structure of super-cooled liquids and glasses. …
Daniele Coslovich, Robert L. Jack, Joris Paret
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Hidden order in disordered materials
When cooled down below their melting temperature, liquids undergo a phase transition to a stable crystalline state, where atoms …
Joris Paret
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partycls: A Python package for structural clustering
partycls is a Python framework for cluster analysis of systems of interacting particles. By grouping particles that share similar …
Joris Paret, Daniele Coslovich
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Assessing the structural heterogeneity of supercooled liquids through community inference
We present an information-theoretic approach inspired by distributional clustering to assess the structural heterogeneity of …
Joris Paret, Robert L. Jack, Daniele Coslovich
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