{"repo":"sylvesterkaczmarek/xlstm-telemetry-assurance","free":true,"listed":false,"github":"https://github.com/sylvesterkaczmarek/xlstm-telemetry-assurance","clone":"git clone https://github.com/sylvesterkaczmarek/xlstm-telemetry-assurance.git","description":"Controlled PyTorch experiments testing xLSTM-style streaming forecasting and runtime assurance under telemetry faults, distribution shift and guarded adaptation.","language":"Python","stars":17,"topics":["anomaly-detection","edge-ai","physical-ai","pytorch","robotics","runtime-assurance","spacecraft-autonomy","telemetry","time-series","xlstm"],"license":"MIT","category":"analytics","readme_excerpt":"xLSTM Telemetry Assurance Controlled PyTorch experiments testing whether an xLSTM-style streaming forecaster can provide useful prediction and runtime-assurance signals under telemetry faults, distribution shift and guarded adaptation. Spacecraft telemetry is the flagship physical-system track, with robotics used as a transfer test. The project deliberately sits between fundamental sequence modelling and physical-world autonomy. It does not turn a generic forecasting demo into a \"space AI\" project by relabelling the data. The benchmark makes physical-system constraints part of the experiment: missing telemetry, sensor corruption, slow drift, abrupt regime changes, uncertainty calibration, online adaptation and rollback. At a glance Project overview - Spacecraft track: coupled power, thermal, reaction-wheel, pointing and payload telemetry. - Robotics track: joint motion, motor current and temperature, vibration and tool load. - Faults: packet loss, spikes, stuck sensors, gradual drift, regime shift and a mixed-fault stream. - Forecasting: ordinary LSTM versus a compact stabilized xLSTM/sLSTM-style recurrent model. - Uncertainty: per-channel Gaussian mean and predictive scale trained with negative log-likelihood. - Runtime assurance: anomaly scores from uncertainty-normalized residuals plus explicit missingness. - Adaptation: head-only candidate updates accepted only when a disjoint guard buffer does not degrade beyond tolerance. - Reproducibility: deterministic generators, fix","default_branch":null,"files":null,"tree":[],"storefront":"/r/sylvesterkaczmarek","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/sylvesterkaczmarek/xlstm-telemetry-assurance/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}