Risi Kondor

Affiliations:
  • The University of Chicago, Department of Computer Science
  • California Institute of Technology, Center for the Mathematics of Information
  • University College London, Gatsby Computational Neuroscience Unit
  • Columbia University, Machine Learning Lab


According to our database1, Risi Kondor authored at least 46 papers between 2002 and 2022.

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Bibliography

2022
On the Super-exponential Quantum Speedup of Equivariant Quantum Machine Learning Algorithms with SU(d) Symmetry.
CoRR, 2022

Temporal Multiresolution Graph Neural Networks For Epidemic Prediction.
CoRR, 2022

Symmetry Group Equivariant Architectures for Physics.
CoRR, 2022

Permutation Equivariant Layers for Higher Order Interactions.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Speeding up Learning Quantum States through Group Equivariant Convolutional Quantum Ans{ä}tze.
CoRR, 2021

Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs.
CoRR, 2021

Multiresolution Graph Variational Autoencoder.
CoRR, 2021

ATOM3D: Tasks on Molecules in Three Dimensions.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Autobahn: Automorphism-based Graph Neural Nets.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fourier Bases for Solving Permutation Puzzles.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
ATOM3D: Tasks On Molecules in Three Dimensions.
CoRR, 2020

A community-powered search of machine learning strategy space to find NMR property prediction models.
CoRR, 2020

The general theory of permutation equivarant neural networks and higher order graph variational encoders.
CoRR, 2020

Lorentz Group Equivariant Neural Network for Particle Physics.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Asymmetric Multiresolution Matrix Factorization.
CoRR, 2019

Deep Learning for Automated Classification and Characterization of Amorphous Materials.
CoRR, 2019

Cormorant: Covariant Molecular Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Effective Resistance-based Germination of Seed Sets for Community Detection.
CoRR, 2018

N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials.
CoRR, 2018

Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups.
Proceedings of the 35th International Conference on Machine Learning, 2018

Covariant Compositional Networks For Learning Graphs.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Multiresolution Kernel Approximation for Gaussian Process Regression.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

The Incremental Multiresolution Matrix Factorization Algorithm.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Data mining when each data point is a network.
CoRR, 2016

The Multiscale Laplacian Graph Kernel.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Multiresolution Matrix Compression.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
SnFFT: a Julia toolkit for Fourier analysis of functions over permutations.
J. Mach. Learn. Res., 2015

Parallel MMF: a Multiresolution Approach to Matrix Computation.
CoRR, 2015

2014
Permutation Diffusion Maps (PDM) with Application to the Image Association Problem in Computer Vision.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Multiresolution Matrix Factorization.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Solving the multi-way matching problem by permutation synchronization.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012
Multiresolution analysis on the symmetric group.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2010
Graph Kernels.
J. Mach. Learn. Res., 2010

A Fourier Space Algorithm for Solving Quadratic Assignment Problems.
Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010

Ranking with Kernels in Fourier space.
Proceedings of the COLT 2010, 2010

2009
The graphlet spectrum.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
The skew spectrum of graphs.
Proceedings of the Machine Learning, 2008

2007
Multi-object tracking with representations of the symmetric group.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

A complete set of rotationally and translationally invariant features for images
CoRR, 2007

2006
Gaussian and Wishart Hyperkernels.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2004
Probability Product Kernels.
J. Mach. Learn. Res., 2004

2003
A Kernel Between Sets of Vectors.
Proceedings of the Machine Learning, 2003

Kernels and Regularization on Graphs.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

Bhattacharyya Expected Likelihood Kernels.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
Diffusion Kernels on Graphs and Other Discrete Input Spaces.
Proceedings of the Machine Learning, 2002


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