Siyuan Guo

According to our database, Siyuan Guo authored at least 18 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

TabPFN-3: Technical Report.

Léo Grinsztajn, Klemens Flöge, Oscar Key, Felix Birkel, Philipp Jund, Brendan Roof, Mihir Manium, Shi Bin Hoo, Magnus Bühler, Anurag Garg, Dominik Safaric, Jake Robertson, Benjamin Jäger, Simone Alessi, Adrian Hayler, Vladyslav Moroshan, Lennart Purucker, Philipp Singer, Alan Arazi, Julien Siems, Jan Hendrik Metzen, Georg Grab, Nick Erickson, Siyuan Guo, Eliott Kalfon, Simon Bing, David Salinas, Clara Cornu, Lilly Charlotte Wehrhahn, Diana Kriuchkova, Kursat Kaya, Lydia Sidhoum, Marie Salmon, Jerry Chen, Madelon Hulsebos, Yann LeCun, Samuel Müller, Bernhard Schölkopf, Sauraj Gambhir, Noah Hollmann, Frank Hutter

CoRR, May, 2026

On the Emergence and Test-Time Use of Structural Information in Large Language Models.

Michelle Chao Chen, Moritz Miller, Bernhard Schölkopf, Siyuan Guo

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

Physics of Learning: A Lagrangian perspective to different learning paradigms.

Siyuan Guo, Bernhard Schölkopf

CoRR, September, 2025

Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning.

Patrik Reizinger, Bálint Mucsányi, Siyuan Guo, Benjamin Eysenbach, Bernhard Schölkopf, Wieland Brendel

CoRR, July, 2025

Do-PFN: In-Context Learning for Causal Effect Estimation.

Jake Robertson, Arik Reuter, Siyuan Guo, Noah Hollmann, Frank Hutter, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Counterfactual reasoning: an analysis of in-context emergence.

Moritz Miller, Bernhard Schölkopf, Siyuan Guo

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning.

Patrik Reizinger, Siyuan Guo, Ferenc Huszár, Bernhard Schölkopf, Wieland Brendel

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Learning Beyond Pattern Matching? Assaying Mathematical Understanding in LLMs.

Siyuan Guo, Aniket Didolkar, Nan Rosemary Ke, Anirudh Goyal, Ferenc Huszár, Bernhard Schölkopf

CoRR, 2024

Do Finetti: On Causal Effects for Exchangeable Data.

Siyuan Guo, Chi Zhang, Karthika Mohan, Ferenc Huszar, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving.

Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo Jimenez Rezende, Yoshua Bengio, Michael C. Mozer, Sanjeev Arora

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Out-of-Variable Generalisation for Discriminative Models.

Siyuan Guo, Jonas Bernhard Wildberger, Bernhard Schölkopf

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Pragmatic Fairness: Developing Policies with Outcome Disparity Control.

Limor Gultchin, Siyuan Guo, Alan Malek, Silvia Chiappa, Ricardo Silva

Proceedings of the Causal Learning and Reasoning, 2024

CausalCite: A Causal Formulation of Paper Citations.

Ishan Kumar, Zhijing Jin, Ehsan Mokhtarian, Siyuan Guo, Yuen Chen, Negar Kiyavash, Mrinmaya Sachan, Bernhard Schölkopf

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Out-of-Variable Generalization.

Siyuan Guo, Jonas Wildberger, Bernhard Schölkopf

CoRR, 2023

Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data.

Siyuan Guo, Viktor Tóth, Bernhard Schölkopf, Ferenc Huszar

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.

Jonas Bernhard Wildberger, Siyuan Guo, Arnab Bhattacharyya, Bernhard Schölkopf

Proceedings of the Conference on Causal Learning and Reasoning, 2023

Dataflow graphs as complete causal graphs.

Andrei Paleyes, Siyuan Guo, Bernhard Schölkopf, Neil D. Lawrence

Proceedings of the 2nd IEEE/ACM International Conference on AI Engineering, 2023

2020

Teams Frightened of Failure Fail More: Modelling Reward Sensitivity in Teamwork.

Siyuan Guo, Soo Ling Lim, Peter J. Bentley

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020