Dingling Yao
6 Publications
2025 | Published | Conference Paper | IST-REx-ID: 20032 |
Chen J, Yao D, Pervez AA, Alistarh D-A, Locatello F. 2025. Scalable mechanistic neural networks. 13th International Conference on Learning Representations. ICLR: International Conference on Learning Representations, 63716–63737.
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| arXiv
2025 | Published | Conference Paper | IST-REx-ID: 20592 |
Yao D, Tronarp F, Bosch N. 2025. Propagating model uncertainty through filtering-based probabilistic numerical ODE solvers. Proceedings of the 1st International Conference on Probabilistic Numerics. ProbNum: Conference on Probabilistic Numerics, PMLR, vol. 271.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 14946 |
Yao D, Xu D, Lachapelle S, Magliacane S, Taslakian P, Martius G, Kügelgen J von, Locatello F. 2024. Multi-view causal representation learning with partial observability. 12th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19010 |
Yao D, Rancati D, Cadei R, Fumero M, Locatello F. 2024. Unifying causal representation learning with the invariance principle. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19005 |
Yao D, Muller CJ, Locatello F. 2024. Marrying causal representation learning with dynamical systems for science. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14958 |
Xu D, Yao D, Lachapelle S, Taslakian P, von Kügelgen J, Locatello F, Magliacane S. 2023. A sparsity principle for partially observable causal representation learning. Causal Representation Learning Workshop at NeurIPS 2023. CRL: Causal Representation Learning Workshop at NeurIPS, 54.
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6 Publications
2025 | Published | Conference Paper | IST-REx-ID: 20032 |
Chen J, Yao D, Pervez AA, Alistarh D-A, Locatello F. 2025. Scalable mechanistic neural networks. 13th International Conference on Learning Representations. ICLR: International Conference on Learning Representations, 63716–63737.
[Published Version]
View
| Files available
| arXiv
2025 | Published | Conference Paper | IST-REx-ID: 20592 |
Yao D, Tronarp F, Bosch N. 2025. Propagating model uncertainty through filtering-based probabilistic numerical ODE solvers. Proceedings of the 1st International Conference on Probabilistic Numerics. ProbNum: Conference on Probabilistic Numerics, PMLR, vol. 271.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 14946 |
Yao D, Xu D, Lachapelle S, Magliacane S, Taslakian P, Martius G, Kügelgen J von, Locatello F. 2024. Multi-view causal representation learning with partial observability. 12th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
[Published Version]
View
| Files available
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19010 |
Yao D, Rancati D, Cadei R, Fumero M, Locatello F. 2024. Unifying causal representation learning with the invariance principle. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.
[Published Version]
View
| Files available
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19005 |
Yao D, Muller CJ, Locatello F. 2024. Marrying causal representation learning with dynamical systems for science. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.
[Published Version]
View
| Files available
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14958 |
Xu D, Yao D, Lachapelle S, Taslakian P, von Kügelgen J, Locatello F, Magliacane S. 2023. A sparsity principle for partially observable causal representation learning. Causal Representation Learning Workshop at NeurIPS 2023. CRL: Causal Representation Learning Workshop at NeurIPS, 54.
[Published Version]
View
| Files available
| Download Published Version (ext.)