NeuroSymbolic

SHAP KernelExplainer takes ~30 ms per prediction (even with a small background) A neuro-symbolic model generates explanations contained in the forward pass in 0.9 ms That’s a 33× speedup with deterministic outputs Fraud recall...

, every metric looked perfect.RWSS = 1.000. Output probabilities unchanged. No labels moved.All the pieces said “all clear.” Then the alert fired anyway. Window 3: severity=warning RWSS=1.000 fired=True ← FIDI Z fires here The model’s predictions didn’t...

systems inject rules written by humans. But what if a neural network could discover those rules itself? On this experiment, I extend a hybrid neural network with a differentiable rule-learning module that mechanically extracts...

Abstract datasets are extremely imbalanced, with positive rates below 0.2%. Standard neural networks trained with weighted binary cross-entropy often achieve high ROC-AUC but struggle to discover suspicious transactions under threshold-sensitive metrics. I propose a...

Imandra Inc., the AI company revolutionizing automated logical reasoning, has announced the discharge of ImandraX, its latest advancement in neurosymbolic AI reasoning. This landmark release introduces cutting-edge capabilities in proof automation, counterexample generation, and...

Generative AI has made impressive strides in recent times. It may well write essays, create art, and even compose music. But with regards to getting facts right, it often falls short. It'd confidently inform...

Neuro-symbolic AI is a strand of AI research that has been around for some time but that recently got increasingly more interest. It tackles interesting challenges in AI like attempting to learn with less...