jgrusewski 9c4c97cf8d spec: Supervised Architecture Transfer — 7 concepts from KAN/xLSTM/Diffusion/TGNN/Liquid/TFT/TLOB ...

1. KAN spline activations → adaptive branch gates (learnable activation shape)
2. xLSTM matrix memory → temporal Q-value context (trajectory pattern detection)
3. Diffusion denoising → iterative Q-refinement (uncertainty-conditioned)
4. TGNN gating → cross-branch graph message passing (structural coordination)
5. Liquid RK4 ODE → higher-order training dynamics (adaptive Euler/RK4)
6. TFT quantile outputs → uncertainty-driven exploration (replaces epsilon-greedy)
7. TLOB MBP-10 → direct microstructure injection to order/urgency branches

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-15 08:19:18 +02:00

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infra

feat(infra): GPU training launcher with local/cloud routing

2026-02-23 11:19:58 +01:00

plans

feat(dqn): enable Branching DQN with 45 factored actions (5×3×3)

2026-03-11 22:00:13 +01:00

superpowers

spec: Supervised Architecture Transfer — 7 concepts from KAN/xLSTM/Diffusion/TGNN/Liquid/TFT/TLOB

2026-04-15 08:19:18 +02:00