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06/19/2023
P-tensors: a General Formalism for Constructing Higher Order Message Passing Networks
Several recent papers have recently shown that higher order graph neural...
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02/17/2023
Modeling Polypharmacy and Predicting Drug-Drug Interactions using Deep Generative Models on Multimodal Graphs
Latent representations of drugs and their targets produced by contempora...
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02/17/2023
Multiresolution Graph Transformers and Wavelet Positional Encoding for Learning Hierarchical Structures
Contemporary graph learning algorithms are not well-defined for large mo...
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02/17/2023
Fast Temporal Wavelet Graph Neural Networks
Spatio-temporal signals forecasting plays an important role in numerous ...
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11/14/2022
Group-Equivariant Neural Networks with Fusion Diagrams
Many learning tasks in physics and chemistry involve global spatial symm...
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07/15/2022
On the Super-exponential Quantum Speedup of Equivariant Quantum Machine Learning Algorithms with SU(d) Symmetry
We introduce a framework of the equivariant convolutional algorithms whi...
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05/31/2022
Learning to Represent Programs with Code Hierarchies
Graph neural networks have been shown to produce impressive results for ...
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05/30/2022
Temporal Multiresolution Graph Neural Networks For Epidemic Prediction
In this paper, we introduce Temporal Multiresolution Graph Neural Networ...
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12/14/2021
Speeding up Learning Quantum States through Group Equivariant Convolutional Quantum Ansätze
We develop a theoretical framework for S_n-equivariant quantum convoluti...
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11/02/2021
Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs
Multiresolution Matrix Factorization (MMF) is unusual amongst fast matri...
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06/02/2021
Multiresolution Graph Variational Autoencoder
In this paper, we propose Multiresolution Graph Networks (MGN) and Multi...
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03/02/2021
Autobahn: Automorphism-based Graph Neural Nets
We introduce Automorphism-based graph neural networks (Autobahn), a new ...
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12/07/2020
ATOM3D: Tasks On Molecules in Three Dimensions
Computational methods that operate directly on three-dimensional molecul...
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08/13/2020
A community-powered search of machine learning strategy space to find NMR property prediction models
The rise of machine learning (ML) has created an explosion in the potent...
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06/08/2020
Lorentz Group Equivariant Neural Network for Particle Physics
We present a neural network architecture that is fully equivariant with ...
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04/08/2020
The general theory of permutation equivarant neural networks and higher order graph variational encoders
Previous work on symmetric group equivariant neural networks generally o...
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10/10/2019
Asymmetric Multiresolution Matrix Factorization
Multiresolution Matrix Factorization (MMF) was recently introduced as an...
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09/10/2019
Deep Learning for Automated Classification and Characterization of Amorphous Materials
It is difficult to quantify structure-property relationships and to iden...
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06/06/2019
Cormorant: Covariant Molecular Neural Networks
We propose Cormorant, a rotationally covariant neural network architectu...
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06/24/2018
Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network
Recent work by Cohen et al. has achieved state-of-the-art results for le...
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03/05/2018
N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials
We describe N-body networks, a neural network architecture for learning ...
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02/11/2018
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups
Convolutional neural networks have been extremely successful in the imag...
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01/07/2018
Covariant Compositional Networks For Learning Graphs
Most existing neural networks for learning graphs address permutation in...
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08/07/2017
Multiresolution Kernel Approximation for Gaussian Process Regression
Gaussian process regression generally does not scale to beyond a few tho...
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05/16/2017
The Incremental Multiresolution Matrix Factorization Algorithm
Multiresolution analysis and matrix factorization are foundational tools...
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03/20/2016
The Multiscale Laplacian Graph Kernel
Many real world graphs, such as the graphs of molecules, exhibit structu...
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06/27/2012
Incorporating Domain Knowledge in Matching Problems via Harmonic Analysis
Matching one set of objects to another is a ubiquitous task in machine l...
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01/20/2007