Siyuan Guo

Affiliations:
  • Max Planck Institute for Intelligent Systems, Germany
  • University of Cambridge, UK


According to our database1, Siyuan Guo authored at least 16 papers between 2020 and 2025.

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Bibliography

2025
Physics of Learning: A Lagrangian perspective to different learning paradigms.
CoRR, September, 2025

Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning.
CoRR, July, 2025

Do-PFN: In-Context Learning for Causal Effect Estimation.
CoRR, June, 2025

Counterfactual reasoning: an analysis of in-context emergence.
CoRR, June, 2025

Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
Learning Beyond Pattern Matching? Assaying Mathematical Understanding in LLMs.
CoRR, 2024

Do Finetti: On Causal Effects for Exchangeable Data.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Out-of-Variable Generalisation for Discriminative Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Pragmatic Fairness: Developing Policies with Outcome Disparity Control.
Proceedings of the Causal Learning and Reasoning, 2024

CausalCite: A Causal Formulation of Paper Citations.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Out-of-Variable Generalization.
CoRR, 2023

Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Interventional Kullback-Leibler Divergence.
Proceedings of the Conference on Causal Learning and Reasoning, 2023

Dataflow graphs as complete causal graphs.
Proceedings of the 2nd IEEE/ACM International Conference on AI Engineering, 2023

2020
Teams Frightened of Failure Fail More: Modelling Reward Sensitivity in Teamwork.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020


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