Causality

KAUST Rising Stars in AI: Causal Representation Learning

I was invited to the Rising Stars in AI Symposium to give a talk on our work in Causal Representation Learning.

ICAI Meetup: CITRIS - Causal Identifiability from Temporal Intervened Sequences

I gave an short introduction into causal representation learning and our ICML work "CITRIS".

CI Working Group: Learning Causal Variables from Temporal Observations

I gave an overview on recent advances in causal representation learning and possible relations to causal incentives analysis in AGI safety at the Causal Incentive Working Group.

UAI Invited Talk: Learning Causal Variables from Temporal Sequences with Interventions

I gave an invited talk on our vision for causal representation learning from temporal observations at the First Workshop on Causal Representation Learning at UAI 2022.

ICML Spotlight: CITRIS - Causal Identifiability from Temporal Intervened Sequences

I presented our ICML paper on causal representation learning from temporal observations.

ICAI Meetup: ENCO - Efficient Neural Causal Discovery

I gave an short introduction into causal discovery and our ICLR work "ENCO".

CausalUAI Contributed Talk: Efficient Neural Causal Discovery without Acyclicity Constraints

I gave a contributed talk on our paper "Efficient Neural Causal Discovery".