Anomaly Detection Model Development

Develop and train a time-series anomaly detection model (e.g., LSTM autoencoder, Transformer) using synthetic or provided BESS data with injected thermal runaway precursors. Utilize Weights & Biases to track your experiments, compare different model architectures, and optimize hyperparameters. The model should output an anomaly score for each incoming data point.