Initial implementation: all models, methods, toy and CIFAR experiments

Debug phase. Toy LQ experiments (3 seeds) complete with terminal gradient matching.
Credit bridge matches state bridge on linear system (~0.94 cosine).
CIFAR experiments in progress.

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+# Experiment Notes
+
+## 2026-03-23: Initial Implementation and Experiments
+
+### Setup
+- GPU: NVIDIA RTX A6000 x4 (using GPU 1)
+- PyTorch 2.10.0+cu128
+- All code written from scratch following CLAUDE.md specifications
+
+### Phase A: Toy LQ Sanity Check
+- Status: Running...
+- Config: d=64, m=10, L=12, sigma=0.03, 5000 steps, batch=256
+- Methods: DFA, State Bridge, Credit Bridge
+
+### Changes Log
+- Created full project structure: models/, methods/, experiments/, metrics/, configs/
+- models/residual_mlp.py: ResidualMLP with pre-LayerNorm residual blocks
+- models/value_net.py: ValueNet V_phi with sinusoidal time embedding
+- models/state_bridge.py: StateBridgeNet G_psi
+- experiments/toy_lq.py: Linear-quadratic sanity check
+- experiments/cifar_resmlp.py: CIFAR-10 main experiment
+- metrics/credit_metrics.py: All diagnostic metrics