The authors extend generative quantum eigensolver to produce circuits with upper-bounded quantum circuit-cutting overhead for molecular ground-state search, tested via transformer decoder on BeH2 with a new loss function and hybrid training strategy.
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R-NP model uses DS-HDP-HMM regime detection plus per-regime CNPs to produce regime-weighted price forecasts that rank as the most balanced option under TOPSIS across 2021-2023 when tested in battery arbitrage and grid-service tasks.
Benchmark study of ten GNN explainers on eight architectures and six datasets that isolates usable components and issues practical recommendations.
The paper summarizes results from the SurgToolLoc and SurgVU challenges held at MICCAI conferences from 2022 to 2025.
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Generative quantum eigensolver with constrained circuit-cutting overhead
The authors extend generative quantum eigensolver to produce circuits with upper-bounded quantum circuit-cutting overhead for molecular ground-state search, tested via transformer decoder on BeH2 with a new loss function and hybrid training strategy.
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Regime-Aware Conditional Neural Processes with Multi-Criteria Decision Support for Operational Electricity Price Forecasting
R-NP model uses DS-HDP-HMM regime detection plus per-regime CNPs to produce regime-weighted price forecasts that rank as the most balanced option under TOPSIS across 2021-2023 when tested in battery arbitrage and grid-service tasks.
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Explaining the Explainers in Graph Neural Networks: a Comparative Study
Benchmark study of ten GNN explainers on eight architectures and six datasets that isolates usable components and issues practical recommendations.
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Intuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025
The paper summarizes results from the SurgToolLoc and SurgVU challenges held at MICCAI conferences from 2022 to 2025.