Thomas Kipf

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Max WellingCAIO CuspAI & Professor Machine Learning, University of AmsterdamVerified email at uva.nl
Aravindh MahendranGoogle DeepmindVerified email at google.com
Rianne van den BergPrincipal Research Manager, Microsoft ResearchVerified email at microsoft.com
Nicola De CaoResearch Scientist at Google DeepMindVerified email at google.com
Klaus GreffResearch Scientist at Google BrainVerified email at usi.ch
Alexey DosovitskiyInceptiveVerified email at inceptive.team
Sjoerd van SteenkisteResearch Scientist at Google ResearchVerified email at google.com
Georg HeigoldResearch Scientist, Google Inc.Verified email at google.com
Ivan TitovUniversity of Edinburgh / University of AmsterdamVerified email at inf.ed.ac.uk
Dirk WeissenbornInceptive Inc.Verified email at inceptive.team
Mehdi S. M. SajjadiResearch Scientist, Google DeepMindVerified email at google.com
Peter BloemVrije Universiteit AmsterdamVerified email at peterbloem.nl
Michael Sejr SchlichtkrullLecturer, Queen Mary University of LondonVerified email at qmul.ac.uk
Francesco LocatelloAssistant Professor, ISTAVerified email at ista.ac.at
Thomas UnterthinerGoogle DeepMindVerified email at pm.me
Jakob UszkoreitInceptiveVerified email at uszkoreit.net
Gamaleldin ElsayedResearch Scientist, Google DeepMindVerified email at google.com
Petar VeličkovićSenior Staff Research Scientist, Google DeepMind | Affiliated Lecturer, University of CambridgeVerified email at google.com
Austin C StoneGoogle DeepMindVerified email at utexas.edu
Elise van der PolMicrosoft ResearchVerified email at microsoft.com

Thomas Kipf

Other namesThomas N. Kipf

Staff Research Scientist, Google DeepMind

Verified email at google.com - Homepage

Machine Learning Graph Representation Learning Graph Neural Networks


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Semi-supervised classification with graph convolutional networks TN Kipf, M Welling International Conference on Learning Representations (ICLR), 2016	43385	2016
Modeling Relational Data with Graph Convolutional Networks M Schlichtkrull, TN Kipf, P Bloem, R Berg, I Titov, M Welling Extended Semantic Web Conference (ESWC), 2017	6315	2017
Variational Graph Auto-Encoders TN Kipf, M Welling NeurIPS Workshop on Bayesian Deep Learning (NeurIPS BDL), 2016	3562	2016
Graph convolutional matrix completion R Berg, TN Kipf, M Welling KDD Deep Learning Day (KDD DLD), 2017	1760*	2017
MolGAN: An implicit generative model for small molecular graphs N De Cao, T Kipf ICML Workshop on Theoretical Foundations and Applications of Deep …, 2018	1250	2018
Neural Relational Inference for Interacting Systems T Kipf, E Fetaya, KC Wang, M Welling, R Zemel International Conference on Machine Learning (ICML), 2018	1098	2018
Object-Centric Learning with Slot Attention F Locatello*, D Weissenborn, T Unterthiner, A Mahendran, G Heigold, ... Advances in Neural Information Processing Systems (NeurIPS), 2020	919	2020
Scaling vision transformers to 22 billion parameters M Dehghani, J Djolonga, B Mustafa, P Padlewski, J Heek, J Gilmer, ... International Conference on Machine Learning (ICML), 2023	605	2023
Simple open-vocabulary object detection with vision transformers M Minderer, A Gritsenko, A Stone, M Neumann, D Weissenborn, ... European Conference on Computer Vision (ECCV), 2022	546*	2022
Hyperspherical Variational Auto-Encoders TR Davidson, L Falorsi, N De Cao*, T Kipf, JM Tomczak Conference on Uncertainty in Artificial Intelligence (UAI), 2018	523	2018
Learned cardinalities: Estimating correlated joins with deep learning A Kipf, T Kipf, B Radke, V Leis, P Boncz, A Kemper Conference on Innovative Data Systems Research (CIDR), 2018	513	2018
Contrastive learning of structured world models T Kipf, E Van der Pol, M Welling International Conference on Learning Representations (ICLR), 2019	340	2019
Towards Sparse Hierarchical Graph Classifiers C Cangea, P Veličković, N Jovanović, T Kipf, P Liò NeurIPS Workshop on Relational Representation Learning (NeurIPS R2L), 2018	329	2018
International conference on learning representations TN Kipf, M Welling International Conference on Learning Representations, 2017	302	2017
Kubric: A scalable dataset generator K Greff, F Belletti, L Beyer, C Doersch, Y Du, D Duckworth, DJ Fleet, ... Conference on Computer Vision and Pattern Recognition (CVPR), 3749-3761, 2022	239	2022
Conditional object-centric learning from video T Kipf, GF Elsayed, A Mahendran, A Stone, S Sabour, G Heigold, ... International Conference on Learning Representations (ICLR), 2021	228	2021
CompILE: Compositional imitation learning and execution T Kipf, Y Li, H Dai, V Zambaldi, A Sanchez-Gonzalez, E Grefenstette, ... International Conference on Machine Learning (ICML), 2019	158	2019
SAVi++: Towards end-to-end object-centric learning from real-world videos GF Elsayed, A Mahendran, S van Steenkiste*, K Greff, MC Mozer, ... Advances in Neural Information Processing Systems (NeurIPS), 2022	150	2022
Object Scene Representation Transformer MSM Sajjadi, D Duckworth, A Mahendran, S van Steenkiste, F Pavetić, ... Advances in Neural Information Processing Systems (NeurIPS), 2022	111	2022
Plannable approximations to mdp homomorphisms: Equivariance under actions E van der Pol, T Kipf, FA Oliehoek, M Welling International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020	97	2020

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