Thomas Kipf

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Max WellingDistinguished Scientist at MSR AI4Science & Professor Machine Learning, University of AmsterdamVerified email at uva.nl
Nicola De CaoResearch Scientist @ Google DeepMindVerified email at google.com
Rianne van den BergPrincipal researcher, Microsoft ResearchVerified email at microsoft.com
Aravindh MahendranGoogle DeepmindVerified email at google.com
Alexey DosovitskiyGoogleVerified email at google.com
Klaus GreffResearch Scientist at Google BrainVerified email at usi.ch
Ivan TitovUniversity of Edinburgh / University of AmsterdamVerified email at inf.ed.ac.uk
Georg HeigoldResearch Scientist, Google Inc.Verified email at google.com
Peter BloemVrije Universiteit AmsterdamVerified email at peterbloem.nl
Michael Sejr SchlichtkrullPostdoctoral Research Associate, University of CambridgeVerified email at cst.cam.ac.uk
Dirk WeissenbornInceptive Inc.Verified email at inceptive.team
Jakob UszkoreitInceptiveVerified email at uszkoreit.net
Sjoerd van SteenkisteResearch Scientist at Google ResearchVerified email at google.com
Petar VeličkovićStaff Research Scientist, Google DeepMind | Affiliated Lecturer, University of CambridgeVerified email at deepmind.com
Jakub M. TomczakAssociate professor at Eindhoven University of TechnologyVerified email at tue.nl
Francesco LocatelloAssistant Professor, ISTAVerified email at ista.ac.at
Thomas UnterthinerGoogle Research (Brain Team)Verified email at pm.me
Elise van der PolMicrosoft ResearchVerified email at microsoft.com
Gamaleldin ElsayedSenior Research Scientist, Google Research, Brain TeamVerified email at google.com
Andreas KipfSenior Applied Scientist, Amazon Web ServicesVerified email at amazon.com

Thomas Kipf

Other namesThomas N. Kipf

Senior Research Scientist, Google DeepMind

Verified email at google.com - Homepage

Machine Learning Graph Representation Learning Graph Neural Networks


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Semi-supervised classification with graph convolutional networks TN Kipf, M Welling International Conference on Learning Representations (ICLR), 2016	29303	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	4335	2017
Variational Graph Auto-Encoders TN Kipf, M Welling NeurIPS Workshop on Bayesian Deep Learning (NeurIPS BDL), 2016	3308*	2016
Graph convolutional matrix completion R Berg, TN Kipf, M Welling KDD Deep Learning Day (KDD DLD), 2017	1345	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	917	2018
Neural Relational Inference for Interacting Systems T Kipf, E Fetaya, KC Wang, M Welling, R Zemel International Conference on Machine Learning (ICML), 2018	826	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	528	2020
Hyperspherical Variational Auto-Encoders TR Davidson, L Falorsi, N De Cao*, T Kipf, JM Tomczak Conference on Uncertainty in Artificial Intelligence (UAI), 2018	406	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	368	2018
Contrastive learning of structured world models T Kipf, E Van der Pol, M Welling International Conference on Learning Representations (ICLR), 2019	257	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	242	2018
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	166*	2022
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	134	2023
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	121	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	105	2019
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	72	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	72	2020
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	63	2022
Object Scene Representation Transformer MSM Sajjadi, D Duckworth, A Mahendran, S van Steenkiste, F Pavetić, ... Advances in Neural Information Processing Systems (NeurIPS), 2022	47	2022
Estimating cardinalities with deep sketches A Kipf, D Vorona, J Müller, T Kipf, B Radke, V Leis, P Boncz, T Neumann, ... Proceedings of the 2019 International Conference on Management of Data, 1937 …, 2019	43	2019

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