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New language unifies relational queries with neural computation

By PulseAugur Editorial · [3 sources] ·

Researchers have introduced Neuro-Relational Programs (NRPs), a novel declarative query language designed to unify relational reasoning with neural computation over structured data. NRPs extend Datalog-style rules to incorporate numeric vector embeddings, enabling the interleaving of relational logic and learnable neural components within a single framework. This approach allows NRPs to function as both trainable query plans and relational-structured neural architectures, offering a general method for neural computation on relational databases. AI

IMPACT This framework could enable more sophisticated and integrated AI models for structured data analysis.

RANK_REASON The cluster contains a research paper detailing a new formalism for querying and neural computation over structured data.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

COVERAGE [3]

  1. arXiv cs.LG TIER_1 English(EN) · Arie Soeteman, Balder ten Cate, Maurice Funk, Benny Kimelfeld, Carsten Lutz, Moritz Sch\"onherr ·

    Neuro-Relational Programs: Unifying Queries and Neural Computation over Structured Data

    arXiv:2606.11946v1 Announce Type: cross Abstract: The conventional approach to deep learning over relational databases applies neural models, such as Graph Neural Networks (GNNs), to a graph representation of the database. Recent approaches instead operate on databases directly, …

  2. arXiv cs.LG TIER_1 English(EN) · Moritz Schönherr ·

    Neuro-Relational Programs: Unifying Queries and Neural Computation over Structured Data

    The conventional approach to deep learning over relational databases applies neural models, such as Graph Neural Networks (GNNs), to a graph representation of the database. Recent approaches instead operate on databases directly, associating tuples with embeddings and extending q…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    Neuro-Relational Programs: Unifying Queries and Neural Computation over Structured Data

    The conventional approach to deep learning over relational databases applies neural models, such as Graph Neural Networks (GNNs), to a graph representation of the database. Recent approaches instead operate on databases directly, associating tuples with embeddings and extending q…

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