VQC architectures that produce full demand probability distributions instead of point forecasts. Born machine interpretation, MMD training, and barren plateau mitigation at SKU/channel/day granularity.
Full-day workshop on VQC architectures for probabilistic demand forecasting in logistics. Covers Born machine interpretation, SKU-level distribution generation, training via MMD loss, and honest assessment of barren plateaus and NISQ noise impact.
Point forecasts tell logistics planners a single number. Probabilistic forecasts tell them the full range of likely outcomes, enabling better safety stock decisions, service level guarantees, and capacity planning. Variational quantum circuits (VQCs) are parameterised quantum circuits that can be trained to generate probability distributions directly: measurement statistics from a VQC output naturally form a discrete probability distribution (the Born machine interpretation). This workshop teaches participants to design VQC architectures for logistics demand forecasting at SKU, channel, and daily granularity. The circuit design trade-off between expressibility and trainability (Sim et al. 2019) determines which distributions a given VQC can represent. Training uses maximum mean discrepancy (MMD) loss to match empirical demand distributions, benchmarked against quantile regression, DeepAR, and Gaussian processes using CRPS (continuous ranked probability score). The workshop is direct about current limitations. Barren plateaus (Cerezo et al. 2021) cause gradient vanishing in deep circuits, making training difficult beyond roughly 10-15 qubits with current optimisers. NISQ device noise corrupts output distributions in ways that standard error mitigation only partially addresses. Classical alternatives (normalising flows, variational autoencoders) produce equivalent probabilistic forecasts without quantum hardware. The workshop maps precisely where VQC forecasting may offer advantage as hardware scales.
Full Day Workshop structure with scheduled breaks. Content is configurable to your organisation's forecasting maturity, SKU granularity, and ML infrastructure.
| # | Session | Topics |
|---|---|---|
| 1 | Point Forecasts Are Not Enough Why logistics needs probabilistic demand distributions, not single numbers | |
| 2 | Variational Quantum Circuit Architecture Parameterised circuits as probabilistic distribution generators |
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| Break, after 60 min | ||
| 3 | Logistics Applications of VQC Forecasting SKU-level, channel-level, and daily granularity probabilistic models |
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| 4 | Interactive Demonstration Training a VQC for probabilistic demand forecasting |
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| Break, after 90 min | ||
| 5 | Training Challenges and NISQ Constraints Barren plateaus, noise, and what limits VQC forecasting today |
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| 6 | Integration and Adoption Framework Connecting VQC research to production forecasting pipelines | |
| 7 | Q&A and Action Planning | |
Workshops are designed and delivered by QSECDEF in collaboration with sector specialists. All facilitators have direct experience in both quantum technologies and logistics systems.
Workshop design and delivery
QSECDEF brings world-leading expertise in post-quantum cryptography, quantum computing strategy, and defence-grade security assessment. Our advisory membership spans 600+ organisations and 1,200+ professionals working at the intersection of quantum technologies and critical infrastructure security.
Domain expertise and operational validation
Logistics workshops are co-delivered with sector specialists who bring direct operational experience in logistics organisations. This ensures workshop content is grounded in regulatory, operational, and technical realities specific to the sector.
Sessions are configured around your forecasting granularity, product portfolio complexity, ML infrastructure, and probabilistic modelling maturity. Get in touch to discuss requirements and schedule a date.
Contact UsQuantum technologies are evolving quickly and new developments emerge regularly. This page was last updated on 15/03/2026. For the most current information about course content and suitability for your organisation, we recommend contacting us directly.
