cb6bca4629
3-layer MLP forward (Linear→ELU→Linear→ELU→Linear). Pre-loaded CudaFunction for graph-capture safety per pearl_no_host_branches_in_captured_graph. Oracle test verifies bit-for-bit match against numpy reference within 1e-4 tol. Saves h_aux1 and h_aux2 to global memory for backward. Phase C.3 of SP14 Layer C separate-aux-trunk refactor (plan: docs/superpowers/plans/2026-05-07-sp14-layer-c-separate-aux-trunk.md). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
ml
10-model ML ensemble for the Foxhunt HFT system, built on Candle v0.9.1.
Models
- DQN (Rainbow) — deep Q-network with prioritized replay, dueling heads, noisy nets
- PPO — proximal policy optimization with GAE, LSTM policies, clip-higher
- TFT — temporal fusion transformer for multi-horizon forecasting
- Mamba2 — state space model for sequence prediction
- Liquid Networks — biologically inspired networks for non-stationary data
- TLOB — transformer-based limit order book analysis
- KAN — Kolmogorov-Arnold networks
- xLSTM — extended LSTM architecture
- TGGN — temporal graph neural network
- Diffusion — diffusion-based generative model
Key Modules
ensemble— model ensemble coordination and confidence aggregationhyperopt— PSO-based hyperparameter optimization with per-model adapterstrainers— unified training loops (DQN, PPO, supervised)inference—InferenceAdaptertrait for predictioncheckpoint— model checkpointing and restorationevaluation— walk-forward evaluation pipeline
Usage
use ml::dqn::DQN;
use ml::ppo::PpoTrainer;