Two papers accepted at NeurIPS 2023: on how to scale knowledge graph embeddings and treat them as generative models (as oral!) and on formalizing, understanding and mitigating reasoning shortcuts in neuro-symbolic AI.

Emile van Krieken and Christian Beltran Jimenez join APRIL as postdoc and PhD student. Welcome!

Antonio’s ERC Starting grant UNREAL (now UKRI Guarantee grant) has started and investigate the next generation of provably reliable probabilistic models and programs in the next five years.

Negative Mixture Models and Unifying and Understanding Overparameterized Circuit Representations via Low-Rank Tensor Decompositions accepted at TPM 2023@UAI.

New preprint on Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts.

New preprint on How to Turn Your Knowledge Graph Embeddings into Generative Models via Probabilistic Circuits.

Inferring mood disorder symptoms from multivariate time-series sensory data accepted at the Workshop on Learning from Time Series for Health, NeurIPS 2022.

Semantic Probabilistic Layers accepted at NeurIPS 2022.

The Dagstuhl Seminar on “Recent Advancements in Tractable Probabilistic Inference” co-organized with Max Welling, Kristian Kersting and Priyank Jaini ended very well!