Urmi Ninad

According to our database, Urmi Ninad authored at least 13 papers between 2022 and 2026.

Collaborative distances:

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

2026

Learning Causal Structure of Time Series using Best Order Score Search.

Irene Gema Castillo Mansilla, Urmi Ninad

CoRR, March, 2026

2025

Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery.

Rebecca Herman, Jonas Wahl, Urmi Ninad, Jakob Runge

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

SPACETIME: Causal Discovery from Non-Stationary Time Series.

Sarah Mameche, Lénaïg Cornanguer, Urmi Ninad, Jilles Vreeken

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Invariance & Causal Representation Learning: Prospects and Limitations.

Simon Bing, Tom Hochsprung, Jonas Wahl, Urmi Ninad, Jakob Runge

Trans. Mach. Learn. Res., 2024

Causal discovery with endogenous context variables.

Wiebke Günther, Oana-Iuliana Popescu, Martin Rabel, Urmi Ninad, Andreas Gerhardus, Jakob Runge

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions.

Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge

Proceedings of the Causal Learning and Reasoning, 2024

2023

Invariance & Causal Representation Learning: Prospects and Limitations.

Simon Bing, Jonas Wahl, Urmi Ninad, Jakob Runge

CoRR, 2023

Projecting infinite time series graphs to finite marginal graphs using number theory.

Andreas Gerhardus, Jonas Wahl, Sofia Faltenbacher, Urmi Ninad, Jakob Runge

CoRR, 2023

Discovering Causal Relations and Equations from Data.

Gustau Camps-Valls, Andreas Gerhardus, Urmi Ninad, Gherardo Varando, Georg Martius, Emili Balaguer-Ballester, Ricardo Vinuesa, Emiliano Diaz, Laure Zanna, Jakob Runge

CoRR, 2023

Increasing effect sizes of pairwise conditional independence tests between random vectors.

Tom Hochsprung, Jonas Wahl, Andreas Gerhardus, Urmi Ninad, Jakob Runge

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Causal Discovery for time series from multiple datasets with latent contexts.

Wiebke Günther, Urmi Ninad, Jakob Runge

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Vector Causal Inference between Two Groups of Variables.

Jonas Wahl, Urmi Ninad, Jakob Runge

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery.

Wiebke Günther, Urmi Ninad, Jonas Wahl, Jakob Runge

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022