Data-driven models in fusion exhaust: AI methods and perspectives

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Data-driven models in fusion exhaust: AI methods and perspectives

Chat with Graph Search

Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population

On the added value of sequential deep learning for the upscaling of evapotranspiration

Enhancing skin lesion classification: a CNN approach with human baseline comparison

Combining physics-based and data-driven models: advancing the frontiers of research with scientific machine learning

Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context

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A Study on Quantum Graph Neural Networks Applied to Molecular Physics

MetaCap: Meta-learning Priors from Multi-view Imagery for Sparse-View Human Performance Capture and Rendering

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

Integrated operation scenarios: Chapter 6 of the special issue: on the path to tokamak burning plasma operation

Transport and confinement physics Chapter 2 of the special issue: on the path to tokamak burning plasma operation

Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE

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Machine Learning in Decision-Making Systems: Fairness, Robustness, and Data Bias

XLSR-Transducer: Streaming ASR for Self-Supervised Pretrained Models

Edge-Cloud Collaborated Object Detection via Bandwidth Adaptive Difficult-Case Discriminator

Introduction and Overview: Chapter 1 of the Special Issue: on the Path to Tokamak Burning Plasma Operation

Directly optimizing for synthesizability in generative molecular design using retrosynthesis models

Performance of the First 80-kA HTS CICC for High-Field Application in Future Fusion Reactors