Alexander Cloninger

Orcid: 0000-0002-1423-9624

According to our database1, Alexander Cloninger authored at least 48 papers between 2013 and 2024.

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Bibliography

2024
Point Cloud Classification via Deep Set Linearized Optimal Transport.
CoRR, 2024

2023
A neural network kernel decomposition for learning multiple steady states in parameterized dynamical systems.
CoRR, 2023

On a Generalization of Wasserstein Distance and the Beckmann Problem to Connection Graphs.
CoRR, 2023

Random Walks, Conductance, and Resistance for the Connection Graph Laplacian.
CoRR, 2023

Semi-Supervised Laplacian Learning on Stiefel Manifolds.
CoRR, 2023

Effective resistance in metric spaces.
CoRR, 2023

Non-degenerate Rigid Alignment in a Patch Framework.
CoRR, 2023

Linearized Wasserstein dimensionality reduction with approximation guarantees.
CoRR, 2023

2022
Classification Logit Two-Sample Testing by Neural Networks for Differentiating Near Manifold Densities.
IEEE Trans. Inf. Theory, 2022

Semi-Supervised Manifold Learning with Complexity Decoupled Chart Autoencoders.
CoRR, 2022

Structure from Voltage.
CoRR, 2022

StreaMRAK a streaming multi-resolution adaptive kernel algorithm.
Appl. Math. Comput., 2022

Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors.
Proceedings of the Topological, 2022


2021
Nonclosedness of sets of neural networks in Sobolev spaces.
Neural Networks, 2021

A deep network construction that adapts to intrinsic dimensionality beyond the domain.
Neural Networks, 2021

LDLE: Low Distortion Local Eigenmaps.
J. Mach. Learn. Res., 2021

Kernel Distance Measures for Time Series, Random Fields and Other Structured Data.
Frontiers Appl. Math. Stat., 2021

On the Dual Geometry of Laplacian Eigenfunctions.
Exp. Math., 2021

SreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm.
CoRR, 2021

Sigma-Delta and Distributed Noise-Shaping Quantization Methods for Random Fourier Features.
CoRR, 2021

A Manifold Learning based Video Prediction approach for Deep Motion Transfer.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

2020
A Witness Function Based Construction of Discriminative Models Using Hermite Polynomials.
Frontiers Appl. Math. Stat., 2020

A low discrepancy sequence on graphs.
CoRR, 2020

Natural Graph Wavelet Packet Dictionaries.
CoRR, 2020

Linear Optimal Transport Embedding: Provable fast Wasserstein distance computation and classification for nonlinear problems.
CoRR, 2020

ReLU nets adapt to intrinsic dimensionality beyond the target domain.
CoRR, 2020

Cautious Active Clustering.
CoRR, 2020

Nonclosedness of the Set of Neural Networks in Sobolev Space.
CoRR, 2020

Coresets for Estimating Means and Mean Square Error with Limited Greedy Samples.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

Variational Diffusion Autoencoders with Random Walk Sampling.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Classification Logit Two-sample Testing by Neural Networks.
CoRR, 2019

Data Sampling for Graph Based Unsupervised Learning: Convex and Greedy Optimization.
CoRR, 2019

Diffusion Variational Autoencoders.
CoRR, 2019

PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
Bounding the Error From Reference Set Kernel Maximum Mean Discrepancy.
CoRR, 2018

Defending against Adversarial Images using Basis Functions Transformations.
CoRR, 2018

2017
Two-sample Statistics Based on Anisotropic Kernels.
CoRR, 2017

2016
Deep Survival: A Deep Cox Proportional Hazards Network.
CoRR, 2016

A Note on Markov Normalized Magnetic Eigenmaps.
CoRR, 2016

2015
Hildreth's algorithm with applications to soft constraints for user interface layout.
J. Comput. Appl. Math., 2015

Provable approximation properties for deep neural networks.
CoRR, 2015

Diffusion Nets.
CoRR, 2015

Bigeometric Organization of Deep Nets.
CoRR, 2015

2014
Solving 2D Fredholm Integral from Incomplete Measurements Using Compressive Sensing.
SIAM J. Imaging Sci., 2014

Operator analysis and diffusion based embeddings for heterogeneous data fusion.
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014

2013
A case study on data fusion with overlapping segments.
Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2013


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