A case study on data fusion with overlapping segments. - Alexander Cloninger; Wojciech Czaja; Timothy Doster (AIPR, 2013)

Operator analysis and diffusion based embeddings for heterogeneous data fusion. - Alexander Cloninger; Wojciech Czaja; Timothy Doster (IGARSS, 2014)

Solving 2D Fredholm Integral from Incomplete Measurements Using Compressive Sensing. - Alexander Cloninger; Wojciech Czaja; Ruiliang Bai; Peter J. Basser (SIAM J. Imaging Sci., 2014)

Exploiting Data-Dependent Structure for Improving Sensor Acquisition and Integration. - Alexander Cloninger (2014)

Bigeometric Organization of Deep Nets. - Alexander Cloninger; Ronald R. Coifman; Nicholas Downing; Harlan M. Krumholz (CoRR, 2015)

Diffusion Nets. - Gal Mishne; Uri Shaham 001; Alexander Cloninger; Israel Cohen (CoRR, 2015)

Provable approximation properties for deep neural networks. - Uri Shaham 001; Alexander Cloninger; Ronald R. Coifman (CoRR, 2015)

Hildreth's algorithm with applications to soft constraints for user interface layout. - Noreen Jamil; Xuemei Chen; Alexander Cloninger (J. Comput. Appl. Math., 2015)

A Note on Markov Normalized Magnetic Eigenmaps. - Alexander Cloninger (CoRR, 2016)

Deep Survival: A Deep Cox Proportional Hazards Network. - Jared Katzman; Uri Shaham 001; Alexander Cloninger; Jonathan Bates; Tingting Jiang; Yuval Kluger (CoRR, 2016)

Two-sample Statistics Based on Anisotropic Kernels. - Xiuyuan Cheng; Alexander Cloninger; Ronald R. Coifman (CoRR, 2017)

Defending against Adversarial Images using Basis Functions Transformations. - Uri Shaham 001; James Garritano; Yutaro Yamada; Ethan Weinberger; Alex Cloninger; Xiuyuan Cheng; Kelly P. Stanton; Yuval Kluger (CoRR, 2018)

Bounding the Error From Reference Set Kernel Maximum Mean Discrepancy. - Alexander Cloninger (CoRR, 2018)

PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems. - Alexander Potapov; Ian Colbert; Kenneth Kreutz-Delgado; Alexander Cloninger; Srinjoy Das (ACSSC, 2019)

Diffusion Variational Autoencoders. - Henry Li; Ofir Lindenbaum; Xiuyuan Cheng; Alexander Cloninger (CoRR, 2019)

Data Sampling for Graph Based Unsupervised Learning: Convex and Greedy Optimization. - Saeed Vahidian; Alexander Cloninger; Baharan Mirzasoleiman (CoRR, 2019)

Classification Logit Two-sample Testing by Neural Networks. - Xiuyuan Cheng; Alexander Cloninger (CoRR, 2019)

Variational Diffusion Autoencoders with Random Walk Sampling. - Henry Li; Ofir Lindenbaum; Xiuyuan Cheng; Alexander Cloninger (ECCV (23), 2020)

Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks. - Ahmed Taha Elthakeb; Prannoy Pilligundla; Fatemeh Mireshghallah; Alexander Cloninger; Hadi Esmaeilzadeh (ICML, 2020)

Coresets for Estimating Means and Mean Square Error with Limited Greedy Samples. - Saeed Vahidian; Baharan Mirzasoleiman; Alexander Cloninger (UAI, 2020)

Nonclosedness of the Set of Neural Networks in Sobolev Space. - Scott Mahan; Emily J. King; Alex Cloninger (CoRR, 2020)

Cautious Active Clustering. - Alexander Cloninger; Hrushikesh N. Mhaskar (CoRR, 2020)

ReLU nets adapt to intrinsic dimensionality beyond the target domain. - Alexander Cloninger; Timo Klock (CoRR, 2020)

Linear Optimal Transport Embedding: Provable fast Wasserstein distance computation and classification for nonlinear problems. - Caroline Moosmüller; Alexander Cloninger (CoRR, 2020)

Natural Graph Wavelet Packet Dictionaries. - Alexander Cloninger; Haotian Li; Naoki Saito 001 (CoRR, 2020)

A low discrepancy sequence on graphs. - Alex Cloninger; Hrushikesh N. Mhaskar (CoRR, 2020)

A Witness Function Based Construction of Discriminative Models Using Hermite Polynomials. - Hrushikesh N. Mhaskar; Xiuyuan Cheng; Alexander Cloninger (Frontiers Appl. Math. Stat., 2020)

A Manifold Learning based Video Prediction approach for Deep Motion Transfer. - Yuliang Cai; Sumit Mohan; Adithya Niranjan; Nilesh Jain; Alex Cloninger; Srinjoy Das (ICCVW, 2021)

Sigma-Delta and Distributed Noise-Shaping Quantization Methods for Random Fourier Features. - Jinjie Zhang; Alexander Cloninger; Rayan Saab (CoRR, 2021)

SreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm. - Andreas Oslandsbotn; Zeljko Kereta; Valeriya Naumova; Yoav Freund; Alexander Cloninger (CoRR, 2021)

On the Dual Geometry of Laplacian Eigenfunctions. - Alexander Cloninger; Stefan Steinerberger (Exp. Math., 2021)

Kernel Distance Measures for Time Series, Random Fields and Other Structured Data. - Srinjoy Das; Hrushikesh N. Mhaskar; Alexander Cloninger (Frontiers Appl. Math. Stat., 2021)

LDLE: Low Distortion Local Eigenmaps. - Dhruv Kohli; Alexander Cloninger; Gal Mishne (J. Mach. Learn. Res., 2021)

A deep network construction that adapts to intrinsic dimensionality beyond the domain. - Alexander Cloninger; Timo Klock (Neural Networks, 2021)

Nonclosedness of sets of neural networks in Sobolev spaces. - Scott Mahan; Emily J. King; Alex Cloninger (Neural Networks, 2021)

Preface. - Alexander Cloninger; Timothy Doster; Tegan Emerson; Manohar Kaul; Ira Ktena; Henry Kvinge; Nina Miolane; Bastian Rice; Sarah Tymochko; Guy Wolf (TAG-ML, 2022)

Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors. - Chester Holtz; Gal Mishne; Alexander Cloninger (TAG-ML, 2022)

StreaMRAK a streaming multi-resolution adaptive kernel algorithm. - Andreas Oslandsbotn; Zeljko Kereta; Valeriya Naumova; Yoav Freund; Alexander Cloninger (Appl. Math. Comput., 2022)

Structure from Voltage. - Robi Bhattacharjee; Alex Cloninger; Yoav Freund (CoRR, 2022)

Semi-Supervised Manifold Learning with Complexity Decoupled Chart Autoencoders. - Stefan C. Schonsheck; Scott Mahan; Timo Klock; Alexander Cloninger; Rongjie Lai (CoRR, 2022)

Classification Logit Two-Sample Testing by Neural Networks for Differentiating Near Manifold Densities. - Xiuyuan Cheng; Alexander Cloninger (IEEE Trans. Inf. Theory, 2022)

Linearized Wasserstein dimensionality reduction with approximation guarantees. - Alexander Cloninger; Keaton Hamm; Varun Khurana; Caroline Moosmüller (CoRR, 2023)

Non-degenerate Rigid Alignment in a Patch Framework. - Dhruv Kohli; Gal Mishne; Alexander Cloninger (CoRR, 2023)

Effective resistance in metric spaces. - Robi Bhattacharjee; Alexander Cloninger; Yoav Freund; Andreas Oslandsbotn (CoRR, 2023)

Semi-Supervised Laplacian Learning on Stiefel Manifolds. - Chester Holtz; Pengwen Chen; Alexander Cloninger; Chung-Kuan Cheng; Gal Mishne (CoRR, 2023)

On a Generalization of Wasserstein Distance and the Beckmann Problem to Connection Graphs. - Sawyer Jack Robertson; Dhruv Kohli; Gal Mishne; Alexander Cloninger (CoRR, 2023)

A neural network kernel decomposition for learning multiple steady states in parameterized dynamical systems. - Yimeng Zhang; Alexander Cloninger; Bo Li; Xiaochuan Tian (CoRR, 2023)

Point Cloud Classification via Deep Set Linearized Optimal Transport. - Scott Mahan; Caroline Moosmüller; Alexander Cloninger (CoRR, 2024)

All You Need is Resistance: On the Equivalence of Effective Resistance and Certain Optimal Transport Problems on Graphs. - Sawyer Jack Robertson; Zhengchao Wan; Alexander Cloninger (CoRR, 2024)

LINSCAN - A Linearity Based Clustering Algorithm. - Andrew Dennehy; Xiaoyu Zou; Shabnam J. Semnani; Yuri Fialko; Alexander Cloninger (CoRR, 2024)

Training Guarantees of Neural Network Classification Two-Sample Tests by Kernel Analysis. - Varun Khurana; Xiuyuan Cheng; Alexander Cloninger (CoRR, 2024)

Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems. - Nicholas Karris; Evangelos A. Nikitopoulos; Ioannis G. Kevrekidis; Seungjoon Lee; Alexander Cloninger (CoRR, 2024)

OTClean: Data Cleaning for Conditional Independence Violations using Optimal Transport. - Alireza Pirhadi; Mohammad Hossein Moslemi; Alexander Cloninger; Mostafa Milani; Babak Salimi (Proc. ACM Manag. Data, 2024)

Random Walks, Conductance, and Resistance for the Connection Graph Laplacian. - Alexander Cloninger; Gal Mishne; Andreas Oslandsbotn; Sawyer Jack Robertson; Zhengchao Wan; Yusu Wang 001 (SIAM J. Matrix Anal. Appl., 2024)

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds. - Jun Linwu; Varun Khurana; Nicholas Karris; Alexander Cloninger (CoRR, 2025)

Robust Graph-Based Semi-Supervised Learning via p-Conductances. - Sawyer Jack Robertson; Chester Holtz; Zhengchao Wan; Gal Mishne; Alexander Cloninger (CoRR, 2025)

Using Causal Inference to Explore Government Policy Impact on Computer Usage. - Mingjia Zhu; Lechuan Wang; Julien Sebot; Bijan Arbab; Babak Salimi; Alexander Cloninger (CoRR, 2025)

Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights. - Zhaiming Shen; Alex Havrilla; Rongjie Lai; Alexander Cloninger; Wenjing Liao (CoRR, 2025)

OT Score: An OT based Confidence Score for Unsupervised Domain Adaptation. - Yiming Zhang; Sitong Liu; Alex Cloninger (CoRR, 2025)

KAIROS: Scalable Model-Agnostic Data Valuation. - Jiongli Zhu; Parjanya Prajakta Prashant; Alex Cloninger; Babak Salimi (CoRR, 2025)