Teams Frightened of Failure Fail More: Modelling Reward Sensitivity in Teamwork. - Siyuan Guo 003; Soo Ling Lim; Peter J. Bentley (SSCI, 2020)

Dataflow graphs as complete causal graphs. - Andrei Paleyes; Siyuan Guo 003; Bernhard Schölkopf; Neil D. Lawrence (CAIN, 2023)

On the Interventional Kullback-Leibler Divergence. - Jonas Bernhard Wildberger; Siyuan Guo 003; Arnab Bhattacharyya 001; Bernhard Schölkopf (CLeaR, 2023)

Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data. - Siyuan Guo 003; Viktor Tóth; Bernhard Schölkopf; Ferenc Huszar (NeurIPS, 2023)

Out-of-Variable Generalization. - Siyuan Guo 003; Jonas Wildberger; Bernhard Schölkopf (CoRR, 2023)

CausalCite: A Causal Formulation of Paper Citations. - Ishan Kumar; Zhijing Jin 001; Ehsan Mokhtarian; Siyuan Guo 003; Yuen Chen; Negar Kiyavash; Mrinmaya Sachan; Bernhard Schölkopf (ACL (Findings), 2024)

Pragmatic Fairness: Developing Policies with Outcome Disparity Control. - Limor Gultchin; Siyuan Guo 003; Alan Malek; Silvia Chiappa; Ricardo Silva 001 (CLeaR, 2024)

Out-of-Variable Generalisation for Discriminative Models. - Siyuan Guo 003; Jonas Bernhard Wildberger; Bernhard Schölkopf (ICLR, 2024)

Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. - Aniket Didolkar; Anirudh Goyal; Nan Rosemary Ke; Siyuan Guo 003; Michal Valko; Timothy P. Lillicrap; Danilo Jimenez Rezende; Yoshua Bengio; Michael C. Mozer; Sanjeev Arora (NeurIPS, 2024)

Do Finetti: On Causal Effects for Exchangeable Data. - Siyuan Guo 003; Chi Zhang; Karthika Mohan; Ferenc Huszar; Bernhard Schölkopf (NeurIPS, 2024)

Learning Beyond Pattern Matching? Assaying Mathematical Understanding in LLMs. - Siyuan Guo 003; Aniket Didolkar; Nan Rosemary Ke; Anirudh Goyal; Ferenc Huszár; Bernhard Schölkopf (CoRR, 2024)

Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning. - Patrik Reizinger; Siyuan Guo 003; Ferenc Huszár; Bernhard Schölkopf; Wieland Brendel (ICLR, 2025)

Counterfactual reasoning: an analysis of in-context emergence. - Moritz Miller; Bernhard Schölkopf; Siyuan Guo 003 (CoRR, 2025)

Do-PFN: In-Context Learning for Causal Effect Estimation. - Jake Robertson; Arik Reuter; Siyuan Guo 003; Noah Hollmann; Frank Hutter; Bernhard Schölkopf (CoRR, 2025)

Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning. - Patrik Reizinger; Bálint Mucsányi; Siyuan Guo 003; Benjamin Eysenbach; Bernhard Schölkopf; Wieland Brendel (CoRR, 2025)

Physics of Learning: A Lagrangian perspective to different learning paradigms. - Siyuan Guo 003; Bernhard Schölkopf (CoRR, 2025)