Active Learning in Gaussian Process State Space Model. - Hon Sum Alec Yu; Dingling Yao; Christoph Zimmer; Marc Toussaint; Duy Nguyen-Tuong (ECML/PKDD (3), 2021)

Multi-View Causal Representation Learning with Partial Observability. - Dingling Yao; Danru Xu; Sébastien Lachapelle; Sara Magliacane; Perouz Taslakian; Georg Martius; Julius von Kügelgen; Francesco Locatello (ICLR, 2024)

A Sparsity Principle for Partially Observable Causal Representation Learning. - Danru Xu; Dingling Yao; Sébastien Lachapelle; Perouz Taslakian; Julius von Kügelgen; Francesco Locatello; Sara Magliacane (ICML, 2024)

Marrying Causal Representation Learning with Dynamical Systems for Science. - Dingling Yao; Caroline Muller; Francesco Locatello (NeurIPS, 2024)

Scalable Mechanistic Neural Networks. - Jiale Chen 004; Dingling Yao; Adeel Pervez; Dan Alistarh; Francesco Locatello (ICLR, 2025)

Unifying Causal Representation Learning with the Invariance Principle. - Dingling Yao; Dario Rancati; Riccardo Cadei; Marco Fumero; Francesco Locatello (ICLR, 2025)

Propagating Model Uncertainty through Filtering-based Probabilistic Numerical ODE Solvers. - Dingling Yao; Filip Tronarp; Nathanael Bosch (CoRR, 2025)

The Third Pillar of Causal Analysis? A Measurement Perspective on Causal Representations. - Dingling Yao; Shimeng Huang; Riccardo Cadei; Kun Zhang 001; Francesco Locatello (CoRR, 2025)