Leena Chennuru Vankadara

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 20

Top Topics

Causal Discovery

Top Venues

Publications

Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
Explaining Kernel Clustering via Decision Trees. CoRR (2024)
Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
Explaining Kernel Clustering via Decision Trees. ICLR (2024)
Leena Chennuru Vankadara, Michael Lohaus, Siavash Haghiri, Faiz Ul Wahab, Ulrike von Luxburg
Insights into Ordinal Embedding Algorithms: A Systematic Evaluation. J. Mach. Learn. Res. 24 (2023)
Dominik Janzing, Philipp Michael Faller, Leena Chennuru Vankadara
Reinterpreting causal discovery as the task of predicting unobserved joint statistics. CoRR (2023)
Philipp Michael Faller, Leena Chennuru Vankadara, Atalanti-Anastasia Mastakouri, Francesco Locatello, Dominik Janzing
Self-Compatibility: Evaluating Causal Discovery without Ground Truth. CoRR (2023)
Luca Rendsburg, Leena Chennuru Vankadara, Debarghya Ghoshdastidar, Ulrike von Luxburg
A Consistent Estimator for Confounding Strength. CoRR (2022)
Leena Chennuru Vankadara, Luca Rendsburg, Ulrike von Luxburg, Debarghya Ghoshdastidar
Interpolation and Regularization for Causal Learning. NeurIPS (2022)
Leena Chennuru Vankadara, Philipp Michael Faller, Michaela Hardt, Lenon Minorics, Debarghya Ghoshdastidar, Dominik Janzing
Causal forecasting: generalization bounds for autoregressive models. UAI (2022)
Leena Chennuru Vankadara, Luca Rendsburg, Ulrike von Luxburg, Debarghya Ghoshdastidar
Interpolation and Regularization for Causal Learning. CoRR (2022)
Mahalakshmi Sabanayagam, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
Graphon based Clustering and Testing of Networks: Algorithms and Theory. ICLR (2022)
Leena Chennuru Vankadara, Sebastian Bordt, Ulrike von Luxburg, Debarghya Ghoshdastidar
Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models. AISTATS (2021)
Mahalakshmi Sabanayagam, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
Graphon based Clustering and Testing of Networks: Algorithms and Theory. CoRR (2021)
Pascal Mattia Esser, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks. CoRR (2021)
Leena Chennuru Vankadara, Sebastian Bordt, Ulrike von Luxburg, Debarghya Ghoshdastidar
Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models. CoRR (2021)
Leena Chennuru Vankadara, Philipp Michael Faller, Lenon Minorics, Debarghya Ghoshdastidar, Dominik Janzing
Causal Forecasting: Generalization Bounds for Autoregressive Models. CoRR (2021)
Leena Chennuru Vankadara, Debarghya Ghoshdastidar
On the optimality of kernels for high-dimensional clustering. AISTATS (2020)
Leena Chennuru Vankadara, Debarghya Ghoshdastidar
On the optimality of kernels for high-dimensional clustering. CoRR (2019)
Siavash Haghiri, Leena Chennuru Vankadara, Ulrike von Luxburg
Large scale representation learning from triplet comparisons. CoRR (2019)
Leena Chennuru Vankadara, Ulrike von Luxburg
Measures of distortion for machine learning. NeurIPS (2018)
Iris Wieser, Sibel Toprak, Andreas Grenzing, Tobias Hinz, Sayantan Auddy, Ethem Can Karaoguz, Abhilash Chandran, Melanie Remmels, Ahmed El Shinawi, Josip Josifovski, Leena Chennuru Vankadara, Faiz Ul Wahab, Alireza MollaAlizadeh Bahnemiri, Debasish Sahu, Stefan Heinrich, Nicolás Navarro-Guerrero, Erik Strahl, Johannes Twiefel, Stefan Wermter
A Robotic Home Assistant with Memory Aid Functionality. KI (2016)