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Found 6 papers, 0 papers with code
Exploring gauge-fixing conditions with gradient-based optimization
Lattice gauge fixing is required to compute gauge-variant quantities, for example those used in RI-MOM renormalization schemes or as objects of comparison for model calculations.
Cross-modulated Attention Transformer for RGBT Tracking
Existing Transformer-based RGBT trackers achieve remarkable performance benefits by leveraging self-attention to extract uni-modal features and cross-attention to enhance multi-modal feature interaction and template-search correlation computation.
Ranked #6 on
Rgb-T Tracking
on GTOT
Exploring Part-Informed Visual-Language Learning for Person Re-Identification
Recently, visual-language learning has shown great potential in enhancing visual-based person re-identification (ReID).
Neural-network preconditioners for solving the Dirac equation in lattice gauge theory
This work develops neural-network--based preconditioners to accelerate solution of the Wilson-Dirac normal equation in lattice quantum field theories.
Representation Bias in Data: A Survey on Identification and Resolution Techniques
Data-driven algorithms are only as good as the data they work with, while data sets, especially social data, often fail to represent minorities adequately.
Applications of Machine Learning to Lattice Quantum Field Theory
There is great potential to apply machine learning in the area of numerical lattice quantum field theory, but full exploitation of that potential will require new strategies.
