Risi Kondor

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Tony JebaraSpotifyVerified email at spotify.com
Gabor CsanyiProfessor of Molecular Modelling, Engineering Laboratory, University of CambridgeVerified email at cam.ac.uk
Albert P. BartokUniversity of WarwickVerified email at warwick.ac.uk
Shubhendu TrivediMassachusetts Institute of TechnologyVerified email at csail.mit.edu
Truong Son HyUniversity of ChicagoVerified email at uchicago.edu
Karsten BorgwardtProfessor, ETH ZurichVerified email at bsse.ethz.ch
Horace PanUniversity of ChicagoVerified email at uchicago.edu
Vikas SinghUniversity of Wisconsin MadisonVerified email at biostat.wisc.edu
Brandon M AndersonAtomwise, Inc.Verified email at jfi.uchicago.edu
Andrew HowardGoogle ResearchVerified email at google.com
S V N VishwanathanAssociate Professor of Statistics and Computer Science, Purdue UniversityVerified email at stat.purdue.edu
Deepti PachauriResearch ScientistVerified email at cs.wisc.edu
Alex SmolaAmazon Web ServicesVerified email at smola.org
Nedelina TenevaUniversity of ChicagoVerified email at uchicago.edu
Pramod Kaushik MudrakartaGoogle ResearchVerified email at google.com
Alexander BogatskiyFlatiron InstituteVerified email at flatironinstitute.org
Zhen LinUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
Vikas K. GargMassachusetts Institute of Technology (MIT)Verified email at mit.edu
Erik ThiedeResearch Fellow, Flatiron InstituteVerified email at flatironinstitute.org
Marconi BarbosaThe Eccles Institute of Neuroscience, John Curtin School of Medical Research, The AustralianVerified email at anu.edu.au

Risi Kondor

Associate Professor, The University of Chicago

Verified email at cs.uchicago.edu - Homepage

Machine Learning Computational Harmonic Analysis Deep Learning Machine Learning for Physics


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Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons AP Bartók, MC Payne, R Kondor, G Csányi Physical review letters 104 (13), 136403, 2010	1627	2010
Diffusion kernels on graphs and other discrete structures RI Kondor, J Lafferty Proceedings of the 19th international conference on machine learning 2002 …, 2002	1510	2002
On representing chemical environments AP Bartók, R Kondor, G Csányi Physical Review B 87 (18), 184115, 2013	1366	2013
Graph kernels SVN Vishwanathan, NN Schraudolph, R Kondor, KM Borgwardt Journal of Machine Learning Research 11, 1201-1242, 2010	1127	2010
Kernels and regularization on graphs AJ Smola, R Kondor Learning theory and kernel machines, 144-158, 2003	997	2003
Probability product kernels T Jebara, R Kondor, A Howard The Journal of Machine Learning Research 5, 819-844, 2004	640	2004
A kernel between sets of vectors R Kondor, T Jebara Proceedings of the 20th international conference on machine learning (ICML …, 2003	349	2003
On the generalization of equivariance and convolution in neural networks to the action of compact groups R Kondor, S Trivedi International Conference on Machine Learning, 2747-2755, 2018	284	2018
Cormorant: Covariant molecular neural networks B Anderson, TS Hy, R Kondor Advances in neural information processing systems 32, 2019	209	2019
Bhattacharyya and expected likelihood kernels T Jebara, R Kondor Learning theory and kernel machines, 57-71, 2003	182	2003
Solving the multi-way matching problem by permutation synchronization D Pachauri, R Kondor, V Singh Advances in neural information processing systems 26, 2013	167	2013
Clebsch–gordan nets: a fully fourier space spherical convolutional neural network R Kondor, Z Lin, S Trivedi Advances in Neural Information Processing Systems 31, 2018	159	2018
The multiscale laplacian graph kernel R Kondor, H Pan Advances in neural information processing systems 29, 2016	153	2016
Group theoretical methods in machine learning IR Kondor Columbia University, 2008	101	2008
Multi-object tracking with representations of the symmetric group R Kondor, A Howard, T Jebara Artificial Intelligence and Statistics, 211-218, 2007	98	2007
N-body networks: a covariant hierarchical neural network architecture for learning atomic potentials R Kondor arXiv preprint arXiv:1803.01588, 2018	89	2018
The graphlet spectrum R Kondor, N Shervashidze, KM Borgwardt Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	84	2009
The skew spectrum of graphs R Kondor, KM Borgwardt Proceedings of the 25th international conference on Machine learning, 496-503, 2008	80	2008
Graph kernels SVN Vishwanathan, KM Borgwardt, IR Kondor, NN Schraudolph arXiv preprint arXiv:0807.0093, 2008	76	2008
Covariant compositional networks for learning graphs R Kondor, HT Son, H Pan, B Anderson, S Trivedi arXiv preprint arXiv:1801.02144, 2018	68	2018

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