Dingling Yao

6 Publications

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[6]
2025 | Published | Conference Paper | IST-REx-ID: 20032 | OA
Chen, Jiale, et al. “Scalable Mechanistic Neural Networks.” 13th International Conference on Learning Representations, ICLR, 2025, pp. 63716–37.
[Published Version] View | Files available | arXiv
 
[5]
2025 | Published | Conference Paper | IST-REx-ID: 20592 | OA
Yao, Dingling, et al. “Propagating Model Uncertainty through Filtering-Based Probabilistic Numerical ODE Solvers.” Proceedings of the 1st International Conference on Probabilistic Numerics, vol. 271, ML Research Press, 2025.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[4]
2024 | Published | Conference Paper | IST-REx-ID: 14946 | OA
Yao, Dingling, et al. “Multi-View Causal Representation Learning with Partial Observability.” 12th International Conference on Learning Representations, Curran Associates, 2024.
[Published Version] View | Files available | arXiv
 
[3]
2024 | Published | Conference Paper | IST-REx-ID: 19010 | OA
Yao, Dingling, et al. “Unifying Causal Representation Learning with the Invariance Principle.” 38th Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.
[Published Version] View | Files available | arXiv
 
[2]
2024 | Published | Conference Paper | IST-REx-ID: 19005 | OA
Yao, Dingling, et al. “Marrying Causal Representation Learning with Dynamical Systems for Science.” 38th Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.
[Published Version] View | Files available | arXiv
 
[1]
2023 | Published | Conference Paper | IST-REx-ID: 14958 | OA
Xu, Danru, et al. “A Sparsity Principle for Partially Observable Causal Representation Learning.” Causal Representation Learning Workshop at NeurIPS 2023, 54, OpenReview, 2023.
[Published Version] View | Files available | Download Published Version (ext.)
 
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6 Publications

Mark all

[6]
2025 | Published | Conference Paper | IST-REx-ID: 20032 | OA
Chen, Jiale, et al. “Scalable Mechanistic Neural Networks.” 13th International Conference on Learning Representations, ICLR, 2025, pp. 63716–37.
[Published Version] View | Files available | arXiv
 
[5]
2025 | Published | Conference Paper | IST-REx-ID: 20592 | OA
Yao, Dingling, et al. “Propagating Model Uncertainty through Filtering-Based Probabilistic Numerical ODE Solvers.” Proceedings of the 1st International Conference on Probabilistic Numerics, vol. 271, ML Research Press, 2025.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[4]
2024 | Published | Conference Paper | IST-REx-ID: 14946 | OA
Yao, Dingling, et al. “Multi-View Causal Representation Learning with Partial Observability.” 12th International Conference on Learning Representations, Curran Associates, 2024.
[Published Version] View | Files available | arXiv
 
[3]
2024 | Published | Conference Paper | IST-REx-ID: 19010 | OA
Yao, Dingling, et al. “Unifying Causal Representation Learning with the Invariance Principle.” 38th Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.
[Published Version] View | Files available | arXiv
 
[2]
2024 | Published | Conference Paper | IST-REx-ID: 19005 | OA
Yao, Dingling, et al. “Marrying Causal Representation Learning with Dynamical Systems for Science.” 38th Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.
[Published Version] View | Files available | arXiv
 
[1]
2023 | Published | Conference Paper | IST-REx-ID: 14958 | OA
Xu, Danru, et al. “A Sparsity Principle for Partially Observable Causal Representation Learning.” Causal Representation Learning Workshop at NeurIPS 2023, 54, OpenReview, 2023.
[Published Version] View | Files available | Download Published Version (ext.)
 
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Citation Style: MLA

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