Leena Chennuru Vankadara

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Debarghya GhoshdastidarTechnical University of MunichEmail verificata su cit.tum.de
Ulrike von LuxburgUniversity of TübingenEmail verificata su informatik.uni-tuebingen.de
Philipp M. FallerKarlsruhe Institute of TechnologyEmail verificata su partner.kit.edu
Dominik JanzingAmazon Development Center, TuebingenEmail verificata su amazon.com
Faiz Ul Wahabsynthavo GmbHEmail verificata su synthavo.de
Pascal M. EsserTechnical University of MunichEmail verificata su in.tum.de
Michael LohausUniversity of TübingenEmail verificata su uni-tuebingen.de
Luca RendsburgUniversity of TübingenEmail verificata su uni-tuebingen.de
Lenon MinoricsAmazon (AWS)Email verificata su amazon.com
Mila HardtManaging Director at the medical data integration center at the University Hospital TübingenEmail verificata su uni-tuebingen.de
Francesco LocatelloAssistant Professor, ISTAEmail verificata su ista.ac.at
Atalanti A. MastakouriApplied Scientist, Amazon Web Services Research/ former Max Planck Institute for Intelligent SystemsEmail verificata su amazon.de
Volkan CevherAssociate Professor, LIONS, EPFL. Amazon Scholar (AGI Foundations).Email verificata su epfl.ch
Moritz HaasPhD Student, University of TübingenEmail verificata su uni-tuebingen.de
Mahalakshmi SabanayagamPhD, Technical University of MunichEmail verificata su tum.de
Jin XuPh.D. Student in Statistics, University of OxfordEmail verificata su stats.ox.ac.uk
Sebastian BordtUniversity of TübingenEmail verificata su uni-tuebingen.de
Maximilian FleissnerPhD at Technical University of MunichEmail verificata su tum.de

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Leena Chennuru Vankadara

Amazon Research; Previously University of Tübingen and Max Planck Institute, Tübingen

Email verificata su uni-tuebingen.de - Home page

Deep learning theory Causal learning theory High-dimensional statistics


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Learning theory can (sometimes) explain generalisation in graph neural networks P Esser, L Chennuru Vankadara, D Ghoshdastidar Advances in Neural Information Processing Systems 34, 27043-27056, 2021	62	2021
Measures of distortion for machine learning L Chennuru Vankadara, U von Luxburg Advances in Neural Information Processing Systems 31, 2018	28	2018
A robotic home assistant with memory aid functionality I Wieser, S Toprak, A Grenzing, T Hinz, S Auddy, EC Karaoğuz, ... KI 2016: Advances in Artificial Intelligence: 39th Annual German Conference …, 2016	17	2016
Insights into ordinal embedding algorithms: A systematic evaluation LC Vankadara, S Haghiri, M Lohaus, FU Wahab, U von Luxburg arXiv preprint arXiv:1912.01666, 2019	16*	2019
On the optimality of kernels for high-dimensional clustering LC Vankadara, D Ghoshdastidar International conference on artificial intelligence and statistics, 2185-2195, 2020	15	2020
Self-compatibility: Evaluating causal discovery without ground truth PM Faller, LC Vankadara, AA Mastakouri, F Locatello, D Janzing International Conference on Artificial Intelligence and Statistics, 4132-4140, 2024	11	2024
Causal forecasting: generalization bounds for autoregressive models LC Vankadara, PM Faller, M Hardt, L Minorics, D Ghoshdastidar, ... Uncertainty in Artificial Intelligence, 2002-2012, 2022	9	2022
Graphon based clustering and testing of networks: Algorithms and theory M Sabanayagam, LC Vankadara, D Ghoshdastidar arXiv preprint arXiv:2110.02722, 2021	8	2021
Reinterpreting causal discovery as the task of predicting unobserved joint statistics D Janzing, PM Faller, LC Vankadara arXiv preprint arXiv:2305.06894, 2023	4	2023
A consistent estimator for confounding strength L Rendsburg, LC Vankadara, D Ghoshdastidar, U von Luxburg arXiv preprint arXiv:2211.01903, 2022	4	2022
Interpolation and regularization for causal learning L Chennuru Vankadara, L Rendsburg, U Luxburg, D Ghoshdastidar Advances in Neural Information Processing Systems 35, 36627-36639, 2022	3	2022
Recovery guarantees for kernel-based clustering under non-parametric mixture models LC Vankadara, S Bordt, U von Luxburg, D Ghoshdastidar International Conference on Artificial Intelligence and Statistics, 3817-3825, 2021	3	2021
Explaining Kernel Clustering via Decision Trees M Fleissner, LC Vankadara, D Ghoshdastidar arXiv preprint arXiv:2402.09881, 2024	2	2024
On feature learning in structured state space models LC Vankadara, J Xu, M Haas, V Cevher The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024	2	2024
: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling M Haas, J Xu, V Cevher, LC Vankadara arXiv preprint arXiv:2411.00075, 2024		2024
A Robotic Home Assistant with Memory Aid Functionality S Auddy, EC Karaoguz, A Chandran, M Remmels, A El Shinawi, ... KI 2016: Advances in Artificial Intelligence: 39th Annual German Conference …, 2016		2016

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