The world we live in is causal, yet many Artificial Intellgience systems and most Machine Learning systems ignore this reality for the sake of convenience. There is a growing interest in making progress in this important concept, and this space will highlight our research in that area.
Our Papers on Causality
- GCRLGenerative Causal Representation Learning for Out-of-Distribution Motion ForecastingIn International Conference on Machine Learning (ICML). Honolulu, Hawaii, USA. Jul, 2023.
- Cyclic causal models with discrete variables: Markov chain equilibrium semantics and sample orderingIn IJCAI International Joint Conference on Artificial Intelligence. Beijing, China. 2013.