D. Neider

Temporal-Causal Inference for Reinforcement Learning via Automata Learning

We consider reinforcement learning in environments with dynamics that undergo an irreversible phase transition governed by a hidden temporal pattern. The agent observes the base state but cannot observe the phase directly. We formalize this problem as a two-phase non-Markovian decision process and introduce Temporal-Ca...

eNNcode: Optimization-Based Analysis of Neural Networks

NoBOOM: Chemical Process Datasets for Industrial Anomaly Detection

NoBOOM is presented, the first collection of datasets for anomaly detection in real-world chemical process data, including labeled data from a running process at BASF SE, one of the world’s leading chemical companies.