causal effect
Causal effect in AI refers to the influence that one variable has on another within a probabilistic model, emphasizing the importance of understanding cause-and-effect relationships for accurate modeling and decision-making.
- A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning
- Coupling Generative Modeling and an Autoencoder with the Causal Bridge
- Disentangling misreporting from genuine adaptation in strategic settings: a causal approach
- Leveraging semantic similarity for experimentation with AI-generated treatments
- Transferring Causal Effects using Proxies
- Turning the Tables: Enabling Backward Transfer via Causal-Aware LoRA in Continual Learning