Graph-native Python reimplementation of the Information Dynamics of Music (IDyOM) model that represents predictive memories as explicit graph objects for musical expectation modeling and network analysis.
Physics-aware end-to-end deep reinforcement learning methodology for quadcopter control with actuator dynamics modeling.
Reinforced Dreamer methodology for asymmetric reinforcement learning using latent guidance to improve world model representations and behaviors in model-based RL.
Relay On-Policy Distillation (Relay-OPD) methodology for trajectory-relayed token-level supervision to overcome prefix failure in reasoning models.
Methodology for identifying and preventing phantom evidence - false positives manufactured by generative AI that appear convincing but lack genuine evidential value due to narrow hypothesis spaces and data leakage.
Gain-Load-Alignment Principle for Dendritic E/I Networks - Framework for understanding when branch-local shunting helps in neural population readout. Analyzes DendriNet architecture with varying integration rules, morphology, and synaptic allocation. Use when…
LLM-powered EEG analysis agent grounded in MNE-Python that separates semantic interpretation from scientific validation using deterministic contracts and confirmation controls to prevent false positives.
Methodology for analyzing and addressing the spectral-temporal dissociation in EEG foundation models that causes cross-population fragility due to blindness to long-range temporal correlations (LRTC).