Bernardo Cuenca Grau
Professor of Computer Science
Works on knowledge representation and reasoning, knowledge graphs, computational logic and graph representation learning.
Bernardo Cuenca Grau's lab at Oxford works on reasoning & neuro-symbolic AI, generative & foundation models and graph mining & networks. 19 papers since 2023, 6 at top venues, mostly ICLR and KR. 9 alumni. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 32%
- PhD students
- 0
- MS students
- 0
- alumni listed
- 9
Papers by yearfrom the lab homepage, 2023–2026
- 1 papers2026 · T1 0 · collecting
- 1 papers2025 · T1 1
- 9 papers2024 · T1 4
- 8 papers2023 · T1 1
T1 venuesOtherVenues: ICLR, KR, AAAI, IJCAI, Journal of Artificial Intelligence Research
Research focuspaper titles that use each topic's words
- Graph mining & networks9 papers
- Generative & foundation models3 papers
- Reasoning & neuro-symbolic AI2 papers
- knowledge1 paper
- representation0 papers
Paper list
From the lab homepage.
20251 paper
20249 papers
- NeurIPS WorkshopAdversarial Attacks as Near−Zero Eigenvalues in the Empirical Kernel of Neural Networks (opens in a new tab)
- NeurIPS WorkshopAlgorithmic Stability of Minimum−Norm Interpolating Deep Neural Networks (opens in a new tab)
- KRBridging Max Graph Neural Networks and Datalog with Negation (opens in a new tab)
- AAAI (T1)Double−descent Curves in Neural Networks: a New Perspective Using Gaussian Processes (opens in a new tab)
- ICLR (T1)Faithful Rule Extraction for Differentiable Rule Learning Models (opens in a new tab)
- ICLR (T1)Faithful Rule Extraction for Differential Rule Learning Models (opens in a new tab)
- KRMTLearn: Extracting Temporal Rules Using Datalog Rule Learners (opens in a new tab)
- ICLR (T1)Orbit−equivariant Graph Neural Networks (opens in a new tab)
- KRRelational Graph Convolutional Networks Do Not Learn Sound Rules (opens in a new tab)
20238 papers
- ECAIAn Empirical Study of Retrieval−enhanced Graph Neural Networks (opens in a new tab)
- IJCAI (T1)Cardinality−Minimal Explanations for Monotonic Neural Networks (opens in a new tab)
- Proceedings of AAAIEfficient Embeddings of Logical Variables for Query Answering over Incomplete Knowledge Graphs (opens in a new tab)
- Journal of Artificial Intelligence ResearchFinite Materialisability of Datalog Programs with Metric Temporal Operators (opens in a new tab)
- Proceedings of AAAIMaterialisation−based Reasoning in DatalogMTL with Bounded Intervals (opens in a new tab)
- Proceedings of the International Conference on the Principles of Knowledge Representation and ReasoningOn the Correspondence Between Monotonic Max−Sum GNNs and Datalog (opens in a new tab)
- JWSStream Reasoning with DatalogMTL (opens in a new tab)
- TPLPThe Stable Models Semantics of Datalog with Metric Temporal Operators (opens in a new tab)
Where alumni went9 listed
Apply to Oxford2027-28
DPhil in Computer Science
- Round
- 2027-28 entry (January round)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Data
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- Papers
- The lab homepage
- Members
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Tiers are venue classifications, not lab rankings.
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