Neural nets  
R. Kondor, Z. Lin and S. Trivedi:
ClebschGordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network (NeurIPS 2018)
R. Kondor:
Nbody networks: a covariant hierarchical neural network architecture for learning
atomic potentials (preprint 3/5/18)
R. Kondor and S. Trivedi:
On the generalization of equivariance and convolution in neural networks to the action of
compact groups (ICML 2018)
R. Kondor, Hy Truong Son, Horace Pan, Brandon Anderson, Shubhendu Trivedi:
Covariant compositional networks for learning graphs (preprint 1/7/18)
[PyTorch code]
[GraphFlow]

Multiresolution Matrix Fact.  
Y. Ding, R. Kondor and J. EskreisWinkler:
Multiresolution kernel approximation for Gaussian process regression (NIPS 2016)
P. K. Mudrakarta and R. Kondor:
A generic multiresolution preconditioner for sparse symmetric systems (preprint)
V. Ithapu, R. Kondor and V. Singh:
The Incremental Multiresolution Matrix Factorization Algorithm
(CVPR 2017)
N. Teneva, P. K. Mudrakarta and R. Kondor:
Multiresolution Matrix Compression
(AISTATS 2016)
R. Kondor, N. Teneva and P. K. Mudrakarta:
pMMF: a high performance C++ library for parallel multiresolution matrix factorization
(Prerelease version)
R. Kondor, N. Teneva and P. K. Mudrakarta:
Parallel MMF: a multiresolution approach to matrix computation
(preprint, July 2015)
R. Kondor, N. Teneva and V. Garg:
Multiresolution matrix factorization (ICML 2014)
[supplement]
[video]

Matching in Vision  
D. Pachauri, R. Kondor, G. Sargur and V. Singh:
Permutation diffusion maps with application to the image association problem in computer vision (NIPS 2014)
D. Pachauri, R. Kondor and V. Singh:
Solving the multiway matching problem by permutation synchronization (NIPS 2013)
D. Pachauri, M. Collins, R. Kondor, V. Singh:
Incorporating domain knowledge in matching problems via harmonic analysis (ICML 2012)

Harmonic Analysis on Sn  
R. Kondor, W. Dempsey:
Multiresolution analysis on the symmetric group (NIPS 2012)
[supplement]
R. Kondor and M. Barbosa:
Ranking with kernels in Fourier space (COLT 2010)
[supplement]
R. Kondor:
A Fourier space algorithm for solving quadratic assignment problems (SODA 2010)

Graph Kernels  
K. Rajendran, A. A. Kattis, A. Holiday, R. Kondor and I. G. Kevrekidis:
Data mining when each data point is a network (preprint)
R. Kondor and H. Pan:
The Multiscale Laplacian Graph Kernel
(NIPS 2016) Oral presentation
[arXiv]
[code]
[slides]
S. V. N. Vishwanathan, N. N. Schraudolf, R. Kondor and K. M. Borgwardt:
Graph kernels (Journal of Machine Learning Research 11, 2010)
[arXiv]
R. Kondor, N. Shervashidze and K. M. Borgwardt:
The graphlet spectrum (ICML 2009)
R. Kondor and K. M. Borgwardt:
The skew spectrum of graphs (ICML 2008)
[ICML video]
[C++ code]

Invariants in Vision  
R. Kondor:
A novel set of rotationally and translationally invariant features for images based on the noncommutative bispectrum (preprint, 2007)
[arXiv]

Molecular descriptors  
A. P. Bartok, R. Kondor and G. Csanyi:
On representing chemical environments (Phys. Rev. B 87, 2013)
[arXiv]
A. P. Bartok, M. C. Payne, R. Kondor and G. Csanyi:
Gaussian Approximation Potentials: the accuracy of quantum mechanics, without the electrons
(Physical Review Letters 104, 2010)
[arXiv]

Tracking  
R. Kondor:
Noncommutative harmonic analysis in multiobject tracking
in "Bayesian Timeseries Models" ed. D. Barber, A. T. Cemgil and S. Chiappa
(Cambridge University Press, 2011)
R. Kondor, A. Howard and T. Jebara:
Multiobject tracking with representations of the symmetric group
(AISTATS 2007)
[Newton video]
[AISPDS video]

Kernels between distributions  
R. Kondor and T. Jebara:
Gaussian and Wishart hyperkernels
(NIPS 2006)
[pdf]
[bib]
T. Jebara, R. Kondor and A. Howard:
Probability product kernels
(Journal of Machine Learning Research 5, 2004)
T. Jebara and R. Kondor:
Bhattacharyya and expected likelihood kernels
(COLT 2003)
[bib]
R. Kondor and T. Jebara:
A kernel between sets of vectors (ICML 2003)
[errata]
[bib]
[note]

Kernels on graphs  
R. Kondor and J.P. Vert:
Diffusion kernels
in "Kernel Methods in Computational Biology" ed. B. Scholkopf, K. Tsuda and J.P. Vert,
(The MIT Press, 2004)
A. Smola and R. Kondor:
Kernels and regularization on graphs
(COLT 2003)
[bib]
R. Kondor and J. Lafferty:
Diffusion kernels on graphs and other discrete input spaces
(ICML 2002)
[bib]

Other preprints  
R. Kondor, G. Csanyi, S. E. Ahnert and T. Jebara:
Multifacet learning in Hilbert spaces (CU tech report, 2005)
R. Kondor:
The skew spectrum of functions on finite groups and their homogeneous spaces (preprint, 2007)
[arXiv]

Thesis  
R. Kondor:
Group theoretical methods in machine learning. (unofficial version)

Software  
R. Kondor:
Mondrian: C++ parallel blocked matrix library
R. Kondor, N. Teneva and P. K. Mudrakarta:
pMMF: a high performance C++ library for parallel multiresolution matrix factorization
R. Kondor:
SnOB: a C++ library for computing fast Fourier transforms on the symmetric group
