Causal-Reasoning-Research-Internship

• Conducted literature research on Causal Machine Learning, CausalRepresentation Learning, Causal Discovery and Neural-Causal AI.
• Developed a score-based, iterative and Gumbell-softmax-based continuous optimisation causal discovery algorithm under the assumption of Gaussian structural equation models with equal error variances. Due to the latter assumption, no interventional data is necessary.
• Developed a variational inference Expectation-Maximisation-like causal discovery algorithm from unknown interventions using an LSTM as an autoregressive distribution over the space of DAGs