Photonicdeepbeam Dataset

PhotonicDeepBeam datasets are original experimental data collected by the DeepBeam/WiNES Lab team at Northeastern University. The data is re-hosted by the QuantBeam project to facilitate reproducibility of research adapting DeepBeam architecture for Photonic-Aware Neural Networks. The dataset's last recorded update was on July 20, 2026.

Use Cases

• Training Photonic-Aware Neural Networks for mmWave beam classification based on experimental wireless data.
• Reproducing and benchmarking results from the QuantBeam project's adaptation of the DeepBeam architecture.
• Studying the performance of neural networks on real-world millimeter-wave beamforming scenarios.

Strengths

• Dataset originates from a known research lab (DeepBeam/WiNES Lab, Northeastern University).
• Explicitly intended for reproducibility of a specific research adaptation (QuantBeam project).
• Last update timestamp is provided (2026-07-20 11:10:50).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

DeepBeam / WiNES Lab team (Polese, Restuccia, Melodia — Northeastern University)

Collection Method

Original experimental datasets collected and published by the research team.

Freshness

Last updated 2026-07-20 11:10:50; freshness should be verified.