Convex and Bilevel Optimization for Neuro-Symbolic Inference and Learning
We address a key challenge for neuro-symbolic (NeSy) systems by leveraging convex and
bilevel optimization techniques to develop a general gradient-based framework for end-to …
bilevel optimization techniques to develop a general gradient-based framework for end-to …
Embed2rule scalable neuro-symbolic learning via latent space weak-labelling
Neuro-symbolic approaches have garnered much interest recently as a path toward
endowing neural systems with robust reasoning capabilities. Most proposed end-to-end …
endowing neural systems with robust reasoning capabilities. Most proposed end-to-end …
LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints
Integrating first-order logic constraints (FOLCs) with neural networks is a crucial but
challenging problem since it involves modeling intricate correlations to satisfy the …
challenging problem since it involves modeling intricate correlations to satisfy the …