🚀 Applications include:
- Safe reinforcement learning
- Logical control in language models
- Temporal reasoning with strong guarantees

Let's discuss! Thoughts, questions, or collaborations? ⬇️ #neurosymbolic #AAAI2025

🙌 @lennertds.bsky.social, @giuseppemarra.bsky.social, @lucderaedt.bsky.social

🔬 In experiments, NeSy-MMs outperform existing neurosymbolic & deep models on both generative & discriminative tasks.

They generalize better to out-of-distribution settings and allow test-time constraint adaptation, making them robust & versatile.

NeSy-MMs integrate:
✅ Relational probabilistic reasoning
✅ Logical constraints
✅ Neural learning
✅ Approximate Bayesian inference

We introduce a novel differentiable particle filter that enables efficient inference & learning while maintaining logical consistency.

Markov models are great for sequential problems, but deep models struggle with constraints, and neurosymbolic AI doesn’t scale.

NeSy-MMs bridge this gap: a new class of differentiable models that provably satisfy relational logical constraints while scaling efficiently.