Debarghya Ghoshdastidar

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Ambedkar DukkipatiProfessor, Department of Computer Science and Automation, Indian Institute of ScienceVerified email at iisc.ac.in
Ulrike von LuxburgUniversity of TübingenVerified email at informatik.uni-tuebingen.de
Pascal M. EsserTechnical University of MunichVerified email at in.tum.de
Leena Chennuru VankadaraAmazon Research; Previously University of Tübingen and Max Planck Institute, TübingenVerified email at uni-tuebingen.de
Mahalakshmi SabanayagamPhD, Technical University of MunichVerified email at tum.de
Maurilio GutzeitIQTIG BerlinVerified email at iqtig.org
Michaël PerrotResearcher INRIAVerified email at inria.fr
Shalabh BhatnagarProfessor in the Department of Computer Science and Automation, Indian Institute of ScienceVerified email at iisc.ac.in
Siavash HaghiriResearch scientist at ZalandoVerified email at informatik.uni-tuebingen.de
Dominik JanzingAmazon Development Center, TuebingenVerified email at amazon.com
Lenon MinoricsAmazon (AWS)Verified email at amazon.com
Mila HardtManaging Director at the medical data integration center at the University Hospital TübingenVerified email at uni-tuebingen.de
Philipp M. FallerKarlsruhe Institute of TechnologyVerified email at partner.kit.edu
James H. H. ChanAMNHVerified email at amnh.org
Laura Leal-TaixéSenior Research Manager at NVIDIA. Prev. Prof. TU MunichVerified email at tum.de
Vivien BonvinPhD, EPFLVerified email at epfl.ch
Satyaki MukherjeeNational University of SingaporeVerified email at nus.edu.sg
Luca RendsburgUniversity of TübingenVerified email at uni-tuebingen.de
Maximilian FleissnerPhD at Technical University of MunichVerified email at tum.de
Sebastian BordtUniversity of TübingenVerified email at uni-tuebingen.de

Debarghya Ghoshdastidar

Technical University of Munich

Verified email at cit.tum.de - Homepage

Machine learning Statistics Network analysis


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Consistency of spectral hypergraph partitioning under planted partition model D Ghoshdastidar, A Dukkipati The Annals of Statistics 45 (1), 289-315, 2017	105	2017
Consistency of spectral partitioning of uniform hypergraphs under planted partition model D Ghoshdastidar, A Dukkipati Advances in Neural Information Processing Systems 27, 2014	102	2014
Two-sample Hypothesis Testing for Inhomogeneous Random Graphs D Ghoshdastidar, M Gutzeit, A Carpentier, U von Luxburg Annals of Statistics 48 (4), 2208-2229, 2020	67	2020
Two-sample tests for large random graphs using network statistics D Ghoshdastidar, M Gutzeit, A Carpentier, U von Luxburg Conference on Learning Theory (COLT) 65, 954-977, 2017	58	2017
A provable generalized tensor spectral method for uniform hypergraph partitioning D Ghoshdastidar, A Dukkipati International Conference on Machine Learning, 400-409, 2015	56	2015
Uniform hypergraph partitioning: Provable tensor methods and sampling techniques D Ghoshdastidar, A Dukkipati Journal of Machine Learning Research 18 (50), 1-41, 2017	54	2017
Practical methods for graph two-sample testing D Ghoshdastidar, U Von Luxburg Advances in Neural Information Processing Systems 31, 2018	50	2018
Comparison based nearest neighbor search S Haghiri, D Ghoshdastidar, U von Luxburg International Conference on Artificial Intelligence and Statistics (AISTATS …, 2017	43	2017
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	40	2021
Spectral clustering using multilinear SVD: Analysis, approximations and applications D Ghoshdastidar, A Dukkipati Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015	36	2015
Foundations of comparison-based hierarchical clustering D Ghoshdastidar, M Perrot, U von Luxburg Advances in neural information processing systems 32, 2019	33	2019
HOLISMOKES-VII. Time-delay measurement of strongly lensed Type Ia supernovae using machine learning S Huber, SH Suyu, D Ghoshdastidar, S Taubenberger, V Bonvin, ... Astronomy & Astrophysics 658, A157, 2022	24	2022
Smoothed Functional Algorithms for Stochastic Optimization Using q-Gaussian Distributions D Ghoshdastidar, A Dukkipati, S Bhatnagar ACM Transactions on Modeling and Computer Simulation (TOMACS) 24 (3), 1-26, 2014	13	2014
On the optimality of kernels for high-dimensional clustering LC Vankadara, D Ghoshdastidar International conference on artificial intelligence and statistics, 2185-2195, 2020	12	2020
Representation power of graph convolutions: Neural tangent kernel analysis M Sabanayagam, P Esser, D Ghoshdastidar	9	2022
Mixture modeling with compact support distributions for unsupervised learning A Dukkipati, D Ghoshdastidar, J Krishnan 2016 International Joint Conference on Neural Networks (IJCNN), 2706-2713, 2016	9	2016
q-Gaussian based smoothed functional algorithms for stochastic optimization D Ghoshdastidar, A Dukkipati, S Bhatnagar 2012 IEEE International Symposium on Information Theory Proceedings, 1059-1063, 2012	9	2012
New insights into graph convolutional networks using neural tangent kernels M Sabanayagam, P Esser, D Ghoshdastidar arXiv preprint arXiv:2110.04060, 2021	8	2021
Graphon based clustering and testing of networks: Algorithms and theory M Sabanayagam, LC Vankadara, D Ghoshdastidar arXiv preprint arXiv:2110.02722, 2021	8	2021
Causal forecasting: generalization bounds for autoregressive models LC Vankadara, PM Faller, M Hardt, L Minorics, D Ghoshdastidar, ... Uncertainty in Artificial Intelligence, 2002-2012, 2022	7	2022

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