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Preprints

Maximum likelihood estimation for Brownian motion tree models based on one sample

Truell, M., Huetter, J.-C., Squires, C., Zwiernik, P. and Uhler, C.

submitted

[arXiv]

Keywords: graphical models, total positivity
 

A mechanism for producing aligned latent spaces with autoencoders

Jain, S., Radhakrishnan, A. and Uhler, C.

submitted

[arXiv]

Keywords: autoencoders
 

The DeCAMFounder: Non-linear causal discovery in the presence of hidden variables

Agrawal, R., Squires, C., Prasad, N. and Uhler, C.

submitted

[arXiv]

Keywords: causal inference, applications to biology

Efficient permutation discovery in causal DAGs

Squires, C., Amaniampong, J. and Uhler, C.

submitted

[arXiv]

Keywords: causal inference

Joint inference of multiple graphs from matrix polynomials

Novarro, M., Wang, Y., Marques, A.G., Uhler, C. and Segarra, S.

submitted

[arXiv]

Keywords: causal inference, graphical models

Linear convergence and implicit regularization of generalized mirror descent with time-dependent mirrors

Radhakrishnan, A., Belkin, M. and Uhler, C.

submitted

[arXiv]

Keywords: optimization

2022

Simple, fast, and flexible framework for matrix completion with infinite width neural networks

Radhakrishnan, A., Stefanakis, G., Belkin, M. and Uhler, C.

to appear in Proceedings of the National Academy of Sciences, U.S.A.

[arXiv]

Keywords: theory of neural networks, applications to biology

Identifying 3D genome organization in diploid organisms via Euclidean distance geometry

Belyaeva, A., Kubjas, K., Sun, L.J. and Uhler, C.

to appear in SIAM Journal on Mathematics of Data Science

[arXiv]

Keywords: optimization, applications to biology

Causal structure discovery between clusters of nodes induced by latent factors

Squires, C., Yun, A., Nichani, E. and Uhler, C.

to appear in Causal Learning and Reasoning (CLearR 2022).

[arXiv]

Keywords: causal inference, applications to biology

Causal imputation via synthetic interventions

Squires, C., Shen, D., Agarwal, A., Shah, D. and Uhler, C.

to appear in Causal Learning and Reasoning (CLearR 2022).

[arXiv]

Keywords: causal inference, applications to biology

Learning the effective dynamics of complex multiscale systems

Vlachas, P. R., Arampatzis, G., Uhler, C. and Koumoutsakos, P.

to appear in Nature Machine Intelligence

[arXiv]

Keywords: autoencoders, applications to physics

2021

Improved conditional flow models for molecule to image synthesis

Yang, K., Goldman, S., Jin, W., Lu, A., Barzilay, R., Jaakkola, T. and Uhler, C.

Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR2021)

[arXiv]

Keywords: generative modeling, applications to biology

DCI: Learning causal differences between gene regulatory networks

Belyaeva, A., Squires, C. and Uhler, C.

Bioinformatics, 2021, 1-3, 10.1093/bioinformatics/btab167.

[arXiv]

Keywords: causal inference, applications to biology

Total positivity in exponential families with application to binary variables
S. Lauritzen, C. Uhler and P. Zwiernik

Annals of Statistics 49 (2021), pp. 1436-1459

[arXiv]

Keywords: total positivity, algebraic statistics

Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing
Belyaeva, A., Cammarata, L., Radhakrishnan, A., Squires, C., Yang, K. D., Shivashankar, G. V. and Uhler, C.

Nature Communications, 12 (2021) 1024

[journal]

Keywords: causal inference, autoencoders, applications to biology

Matching a desired causal state via shift interventions

Zhang, J., Squires, C. and Uhler, C.

Advances in Neural Information Processing Systems 34 (NeurIPS 2021)

[arXiv]

Keywords: causal inference, applications to biology

Near-optimal multi-perturbation experimental design for causal structure learning

Scott, S., Krause, A. and Uhler, C.

Advances in Neural Information Processing Systems 34 (NeurIPS 2021)

[arXiv]

Keywords: causal inference, applications to biology

Causality in digital medicine
Glocker, B., Musolesi, M., Richens, J. and C. Uhler

Nature Communications 12 (2021), pp. 5471

[arXiv]

Keywords: causality, applications to biology

Maximum likelihood estimation for totally positive log-concave densities
E. Robeva, B. Sturmfels, N. Tran and C. Uhler

Scandinavian Journal of Statistics 48 (2021), pp. 817-844

[arXiv]

Keywords: shape-constrained density estimation, total positivity

Do deeper convolutional networks perform better?

Nichani, E., Radhakrishnan, A. and Uhler, C.

ICML Workshop on "Over-Parameterization: Pitfalls and Opportunities" (ICML 2021)

[arXiv]

Keywords: theory of neural networks

On alignment in deep linear neural networks

Radhakrishnan, A., Nichani, E., Bernstein, D. and Uhler, C.

ICML Workshop on "Over-Parameterization: Pitfalls and Opportunities" (ICML 2021)

[arXiv]

Keywords: theory of neural networks

Local quadratic convergence of stochastic gradient descent with adaptive step size

Radhakrishnan, A., Belkin, M. and Uhler, C.

ICML Workshop on "Over-Parameterization: Pitfalls and Opportunities" (ICML 2021)

[arXiv]

Keywords: theory of neural networks

  

Consistency guarantees for greedy permutation-based causal inference algorithms
L. Solus, Y. Wang, and C. Uhler

Biometrika (2021), asaa104

[arXiv]

Keywords: causal inference, algebraic statistics

Multidomain translation between single-cell imaging and sequencing data using autoencoders
Yang, K. D., Belyaeva, A., Venkatchalapathy, S., Damodaran, K., Radhakrishnan, A., Katcoff, A., Shivashankar, G. V. and Uhler, C.

Nature Communications 12 (2021), article 31

[journal]

Keywords: autoencoders, applications to biology

Mechanogenomic coupling of lung tissue stiffness, EMT and coronavirus pathogenicity
Uhler, C. and Shivashankar, G. V.

Current Opinion in Solid State and Materials Science 25 (2021), pp. 100874

[journal]

Keywords: applications to biology

2020

Ordering-based causal structure learning in the presence of latent variables
D. I. Bernstein, B. Saeed, C. Squires and C. Uhler

Proceedings of Machine Learning Research 108 (AISTATS 2020), pp. 4098-4108

[arXiv]

Keywords: causal inference, algebraic statistics

Permutation-based causal structure learning with unknown intervention targets
C. Squires, Y. Wang and C. Uhler

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI 2020)

[arXiv]

Keywords: causal inference, applications to biology

Causal structure discovery from distributions arising from mixtures of DAGs
Saeed, B., Panigrahi, S. and Uhler, C.,

Proceedings of Machine Learning Research 119 (ICML 2020)

[arXiv]

Keywords: causal inference, applications to biology

Optimal transport using GANs for lineage tracing
Prasad, N., Yang, K.D. and Uhler, C.,

Workshop on Computational Biology, International Conference on Machine Learning (ICML 2020)

[arXiv]

Keywords: autoencoders, optimal transport, applications to biology

Overparameterized neural networks can implement associative memory
A. Radhakrishnan, M. Belkin and C. Uhler

Proceedings of the National Academy of Sciences, U.S.A. 117 (2020), pp. 27162-27170

[journal]

Keywords: autoencoders, machine learning

Covariance matrix estimation under total positivity for portfolio selection
R. Agrawal, U. Roy and C. Uhler

Journal of Financial Econometrics (2020), nbaa018

[arXiv]

Keywords: total positivity, applications to finance

Learning high-dimensional Gaussian graphical models under total positivity without tuning parameters
Y. Wang, U. Roy and C. Uhler

Proceedings of Machine Learning Research 108 (AISTATS 2020), pp. 2698-2708

[arXiv]

Keywords: total positivity, applications to finance

Anchored causal inference in the presence of measurement error
B. Saeed, A. Belyaeva, Y. Wang and C. Uhler

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI 2020)

[arXiv]

Keywords: causal inference, applications to biology
 

Brownian motion tree models are toric
B. Sturmfels, C. Uhler and P. Zwiernik

Kybernetika (special issue for Frantisek Matus) 56 (2020), pp. 1154-1175

[arXiv]

Keywords: total positivity, algebraic statistics

Predicting cell lineages using autoencoders and optimal transport
K.D. Yang, K. Damodaran, S. Venkatchalapathy, A.C. Soylemezoglu, G.V Shivashankar and C. Uhler

PLoS Computational Biology 16 (2020), e1007828

[journal]

Keywords: autoencoders, applications to biology

Mechano-genomic regulation of coronaviruses and its interplay with ageing
Uhler, C. and Shivashankar, G.V.

Nature Reviews Molecular Cell Biology 21 (2020), pp. 247-248

[journal]

Keywords: applications to biology

High-dimensional joint estimation of multiple directed Gaussian graphical models
Y. Wang, S. Segarra and C. Uhler

Electronic Journal of Statistics 14 (2020), pp. 2439-2483

[arXiv]

Keywords: causal inference, high-dimensional statistics

Algebraic statistics in practice: Applications to networks
M. Casanellas, S. Petrovic and C. Uhler

Annual Review of Statistics and its Applications 7 (2020), pp. 227-250 (invited review)

[arXiv]

Keywords: causal inference, algebraic statistics

2019

  

Maximum likelihood estimation in Gaussian models under total positivity
S. Lauritzen, C. Uhler and P. Zwiernik

Annals of Statistics 47 (2019), pp. 1835-1863.

[arXiv]

Keywords: total positivity, Gaussian graphical models

Multi-domain translation by learning uncoupled autoencoders
K.D. Yang and C. Uhler

Computational Biology Workshop, International Conference on Machine Learning (ICML 2019)

[arXiv]

Keywords: autoencoders, machine learning

Memorization in overparameterized autoencoders
A. Radhakrishnan, K.D. Yang, M. Belkin and C. Uhler

Deep Phenomena Workshop, International Conference on Machine Learning (ICML 2019)

[arXiv]

Keywords: autoencoders, machine learning

ABCD-Strategy: Budgeted experimental design for targeted causal structure discovery
R. Agrawal, C. Squires, K.D. Yang, K. Shanmugam and C. Uhler

Proceedings of Machine Learning Research 89 (AISTATS 2019), pp. 3400-3409

[arXiv]

Keywords: causal inference, experimental design

Size of interventional Markov equivalence classes in random DAG models

D. Katz-Rogozhnikov, K. Shanmugam, C. Squires and C. Uhler

Proceedings of Machine Learning Research 89 (AISTATS 2019), pp. 3234-3243

[arXiv]

Keywords: causal inference

Scalable unbalanced optimal transport using generative adversarial networks
K.D. Yang and C. Uhler

International Conference on Learning Representations (ICLR 2019)

[arXiv]

Keywords: optimal transport, applications to biology

Geometry of discrete copulas
E. Perrone, L. Solus and C. Uhler

Journal of Multivariate Analysis 172 (2019), pp. 162-179

[arXiv]

Keywords: algebraic statistics

Loading monotonicity of weighted premiums, and total positivity properties of weight functions
D. Richards and C. Uhler

Journal of Mathematical Analysis and Applications, 475 (2019), pp. 532-553.

[arXiv]

Keywords: mathematical statistics, total positivity

Generalized Fréchet bounds for cell entries in multidimensional contingency tables

C. Uhler and D. Richards

Journal of Algebraic Statistics 10 (special issue for Stephen E. Fienberg) (2019), pp. 1-12

[arXiv]

Keywords: mathematical statistics, total positivity

Geometry of log-concave density estimation
E. Robeva, B. Sturmfels and C. Uhler

Discrete & Computational Geometry 61 (2019), pp. 136-160

[arXiv]

Keywords: shape-constrained density estimation, algebraic statistics

2018

  

Direct estimation of differences in causal graphs
Y. Wang, C. Squires, A. Belyaeva and C. Uhler

Advances in Neural Information Processing Systems 31 (2018)

[arXiv]

Keywords: causal inference, applications to biology

PatchNet: Interpretable neural networks for image classification
A. Radhakrishnan, C. Durham, A. Soylemezoglu and C. Uhler

Machine Learning for Health (ML4H) Workshop, Neural Information Processing Systems (2018)

[arXiv]

Keywords: neural nets, applications to biology

Minimal I-MAP MCMC for scalable structure discovery in causal DAG models
R. Agrawal, T. Broderick and C. Uhler

Proceedings of Machine Learning Research 80 (ICML 2018), pp. 89-98

[arXiv]

Keywords: causal inference, Bayesian statistics, applications to biology

Characterizing and learning equivalence classes of causal DAGs under interventions
K. D. Yang, A. Katcoff and C. Uhler

Proceedings of Machine Learning Research 80 (ICML 2018), pp. 5537-5546

[arXiv]

Keywords: causal inference, applications to biology

Learning directed acyclic graphs based on sparsest permutations
G. Raskutti and C. Uhler

Stat   7 (2018), e183

[arXiv]

Keywords: causal inference, algebraic statistics

Counting Markov equivalence classes for DAG models on trees
A. Radhakrishnan, L. Solus and C. Uhler

Discrete Applied Mathematics  244 (2018), pp. 170-185

[arXiv]

Keywords: causal inference, algebraic statistics

Nuclear mechanopathology and cancer diagnosis
C. Uhler and G.V. Shivashankar

Trends in Cancer  4 (2018), pp. 320-331 (invited review)

[journal]

Keywords: applications to biology, chromosome packing

Generalized permutohedra from probabilistic graphical models
F. Mohammadi, C. Uhler, C. Wang and J. Yu

SIAM Journal on Discrete Mathematics  32 (2018), pp. 64-93

[arXiv]

Keywords: causal inference, algebraic statistics

 

Exact formulas for the normalizing constants of Wishart distributions for graphical models
C. Uhler, A. Lenkoski and D. Richards

Annals of Statistics  46 (2018), pp. 90-118

[arXiv]

Keywords: Gaussian graphical models, Bayesian statistics

Gaussian graphical models: An algebraic and geometric perspective

C. Uhler

Chapter for Handbook on Graphical Models  (editors: M. Drton, S. Lauritzen, M. Maathuis and M. Wainwright)

[arXiv]

Keywords: Gaussian graphical models, algebraic statistics

2017

  

Machine learning for nuclear mechano-morphometric biomarkers in cancer diagnosis
A. Radhakrishnan, D. Damodaran, A. Soylemezoglu, C. Uhler, and G.V. Shivashankar

Scientific Reports 7 (2017), article nr. 17946.

[journal]

Keywords: neural nets, applications to biology

Permutation-based causal inference algorithms with interventions

Y. Wang, L. Solus, K.D. Yang and C. Uhler

Advances in Neural Information Processing (NIPS  2017)

[arXiv]

Keywords: causal inference, algebraic statistics 

Network analysis identifies chromosome intermingling regions as regulatory hotspots for transcription
A. Belyaeva, S. Venkatachalapathy, M. Nagarajan, G.V. Shivashankar and C. Uhler

Proceedings of the National Academy of Sciences, U.S.A. 114 (2017), pp. 13714-13719.

[journal]

Keywords: chromosome packing, applications to biology

Regulation of genome organization and gene expression by nuclear mechanotransduction
C. Uhler and G.V. Shivashankar

Nature Reviews Molecular Cell Biology  18 (2017), pp. 717-727  (invited review).

[journal]

Keywords: applications to biology, chromosome packing

Chromosome intermingling: Mechanical hotspots for genome regulation
C. Uhler and G.V. Shivashankar

Trends in Cell Biology  27 (2017), pp. 810-819  (invited review)

[journal]

Keywords: chromosome packing, applications to biology

Orientation and repositioning of chromosomes correlate with cell geometry-dependent gene expression
Y. Wang, M. Nagarajan, C. Uhler and G.V. Shivashankar

Molecular Biology of the Cell  28 (2017), pp. 1997-2009

[journal]

Keywords: chromosome packing, applications to biology

Maximum likelihood estimation for linear Gaussian covariance models
P. Zwiernik, C. Uhler and D. Richards

Journal of the Royal Statistical Society, Series B  79 (2017), pp. 1269-1292

[arXiv]

Keywords: Gaussian models, covariance estimation, optimization

 

Counting Markov equivalence classes by number of immoralities
A. Radhakrishnan, L. Solus and C. Uhler

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence  (UAI 2017)

[arXiv]

Keywords: causal inference, algebraic statistics

 

Total positivity in Markov structures
S. Fallat, L. Lauritzen, K. Sadeghi, C. Uhler, N. Wermuth and P. Zwiernik

Annals of Statistics  45 (2017), pp. 1152-1184

[arXiv]

Keywords: total positivity, mathematical statistics

 

Exact goodness-of-fit testing for the Ising model
A. Martin del Campo, S. Cepeda and C. Uhler

Scandinavian Journal of Statistics  44 (2017), pp. 285-306

[arXiv]

Keywords: hypothesis testing, algebraic statistics
 

2016

 

Extremal positive semidefinite matrices for graphs without K5 minors

L. Solus, C. Uhler and R. Yoshida

Linear Algebra and its Applications  509 (2016), pp. 247-275

[arXiv]

Keywords: Gaussian graphical models, algebraic statistics

Geometric control and modeling of genome reprogramming
C. Uhler and G.V. Shivashankar

BioArchitecture  6 (2016), pp. 76-84

[journal]

Keywords: chromosome packing, applications to biology

 

Exponential varieties

M. Michalek, B. Sturmfels, C. Uhler and P. Zwiernik

Proceedings of the London Mathematical Society  112 (2016), pp. 27-56

[arXiv]

Keywords: Gaussian graphical models, algebraic statistics

2015

 

Faithfulness and learning of hypergraphs from discrete distributions

A. Klimova, C. Uhler and T. Rudas

Journal of Computational Statistics and Data Analysis  87 (2015), pp. 57-72.

[arXiv]

Keywords: causal inference, algebraic statistics

 

2014

 

Hypersurfaces and their singularities in partial correlation testing

S. Lin, C. Uhler, B. Sturmfels and P. Bühlmann

Foundations of Computational Mathematics  14 (2014), pp. 1079-1116

[arXiv]

Keywords: causal inference, algebraic statistics

 

Differentially private logistic regression for detecting multiple-SNP association in GWAS databases

F. Yu, M. Rybar, C. Uhler and S.E. Fienberg

Privacy in Statistical Databases  8744 (2014), pp. 170-184

[arXiv]

Keywords: differential privacy, applications to biology

 

Sphere packing with limited overlap

M. Iglesias-Ham, M. Kerber and C. Uhler

Proceedings of the 26th Canadian Conference on Computational Geometry, Halifax, Nova Scotia (2014), pp. 155-161.

[arXiv]

Keywords: sphere packing, applications to biology

 

Scalable privacy-preserving data sharing methodology for genome-wide association studies

F. Yu, S.E. Fienberg, A. Slavkovic and C. Uhler

Journal of Biomedical Informatics  50 (2014), pp. 133-141

[arXiv]

Keywords: differential privacy, applications to biology

2013

 

Packing ellipsoids with overlap

C. Uhler and S.J. Wright

SIAM Review  55 (2013), pp. 671-706  (selected as Research Spotlight)

[arXiv]

Keywords: optimization, sphere packing, chromosome packing

Geometry of faithfulness assumption in causal inference

C. Uhler, G. Raskutti, P. Bühlmann and B. Yu

Annals of Statistics  41 (2013), pp. 436-463

[arXiv]

Keywords: causal inference, algebraic statistics

 

Privacy-preserving data sharing for genome-wide association studies

C. Uhler, S.E. Fienberg and A. Slavkovic

Journal of Privacy and Confidentiality  5 (2013), pp. 137-166

[arXiv]

Keywords: differential privacy, applications to biology

2012

 

Geometry of maximum likelihood estimation in Gaussian graphical models

C. Uhler

Annals of Statistics  40 (2012), pp. 238-261

[arXiv]

Keywords: Gaussian graphical models, algebraic statistics

2011

 

Privacy preserving GWAS data sharing

S.E. Fienberg, A. Slavkovic and C. Uhler

Proceedings of the 11th IEEE International Conference on Data Mining, Vancouver, Canada (2011), pp. 628-635

[pdf]

Keywords: differential privacy, applications to biology

 

Detecting epistasis via Markov bases

A. Malaspinas and C. Uhler

Journal of Algebraic Statistics  2 (2011), pp. 36-53

[arXiv]

Keywords: algebraic statistics, applications to biology

2010

 

Multivariate Gaussians, semidefinite matrix completion and convex algebraic geometry

B. Sturmfels and C. Uhler

Annals of the Institute of Statistical Mathematics  62 (2010), pp. 603-638

[arXiv]

Keywords: Gaussian graphical models, algebraic statistics

 

Commuting birth-and-death processes

S. Evans, B. Sturmfels and C. Uhler

Annals of Applied Probability  20 (2010), pp. 238-266

[arXiv]

Keywords: birth-and-death processes, algebraic statistics

2009

 

Mastitis in dairy production: Estimation of sensitivity, specificity and disease prevalence in the absence of a gold standard

C. Uhler

Journal of Agricaltural, Biological, and Environmental Statistics  14 (2009),  pp. 79-98

[journal]  [pdf]

Keywords: differential privacy, applications to biology

2008

 

A complete Neandertal mitochondrial genome sequence determined by high-throughput sequencing

R.E. Green, A. Malaspinas, J. Krause, A.W. Briggs, P.L. Johnson, C. Uhler, M. Meyer, J.M. Good, T. Maricic, U. Stenzel, K. Prüfer, M. Siebauer, H.A. Burbano, M. Ronan, J.M. Rothberg, M. Egholm, P. Rudan, D. Brajkovic, Z. Kucan, I. Gusic, M. Wikström, L. Laakkonen, J. Kelso, M. Slatkin and S. Pääbo

Cell  134 (2008), pp. 416-426

[journal]

Keywords: applications to biology
 

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