Claude a7dd31cc2b feat(train): Complete all 5 ruvector integrations — ADR-016 ... All integration points from ADR-016 are now implemented: 1. ruvector-mincut → metrics.rs: DynamicPersonMatcher wraps DynamicMinCut for O(n^1.5 log n) amortized multi-frame person assignment; keeps hungarian_assignment for deterministic proof. 2. ruvector-attn-mincut → model.rs: apply_antenna_attention bridges tch::Tensor to attn_mincut (Q=K=V self-attention, lambda=0.3). ModalityTranslator.forward_t now reshapes CSI to [B, n_ant, n_sc], gates irrelevant antenna-pair correlations, reshapes back. 3. ruvector-attention → model.rs: apply_spatial_attention uses ScaledDotProductAttention over H×W spatial feature nodes. ModalityTranslator gains n_ant/n_sc fields; WiFiDensePoseModel::new computes and passes them. 4. ruvector-temporal-tensor → dataset.rs: CompressedCsiBuffer wraps TemporalTensorCompressor with tiered quantization (hot/warm/cold) for 50-75% CSI memory reduction. Multi-segment tracking via segment_frame_starts prefix-sum index for O(log n) frame lookup. 5. ruvector-solver → subcarrier.rs: interpolate_subcarriers_sparse uses NeumannSolver for O(√n) sparse Gaussian basis interpolation of 114→56 subcarrier resampling with λ=0.1 Tikhonov regularization. cargo check -p wifi-densepose-train --no-default-features: 0 errors. https://claude.ai/code/session_01BSBAQJ34SLkiJy4A8SoiL4		2026-02-28 15:46:22 +00:00
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wifi-densepose-rs	feat(train): Complete all 5 ruvector integrations — ADR-016	2026-02-28 15:46:22 +00:00
SWARM_CONFIG.md	feat: Complete Rust port of WiFi-DensePose with modular crates	2026-01-13 03:11:16 +00:00