The past decade has witnessed significant advances in causal inference and Bayesian network learning, two intertwined disciplines that allow researchers to discern underlying cause‐and‐effect ...

Causal inference is crucial in biological research, as it enables the understanding of complex relationships and dynamic processes that drive cellular behavior, development, and disease. Within this ...

The complex biological processes, such as pericyte-to-neuron transition, pluripotency-to-hepatocyte transition, and epithelial-to-mesenchymal transition, involve pre-transition or critical states ...

The granted patents span innovations in causal inference, large language model (LLM) training, AI-powered correlation, ...