Learning Fine Motion by Markov Mixtures of Experts. - Marina Meila; Michael I. Jordan (NIPS, 1995)

Triangulation by Continuous Embedding. - Marina Meila; Michael I. Jordan (NIPS, 1996)

An Objective Function for Belief Net Triangulation. - Marina Meila; Michael I. Jordan (AISTATS, 1997)

Estimating Dependency Structure as a Hidden Variable. - Marina Meila; Michael I. Jordan (NIPS, 1997)

An Experimental Comparison of Several Clustering and Initialization Methods. - Marina Meila; David Heckerman (UAI, 1998)

An Accelerated Chow and Liu Algorithm: Fitting Tree Distributions to High-Dimensional Sparse Data. - Marina Meila (ICML, 1999)

Maximum Entropy Discrimination. - Tommi S. Jaakkola; Marina Meila; Tony Jebara (NIPS, 1999)

Learning with Mixtures of Trees. - Marina Meila-Predoviciu (1999)

Learning Segmentation by Random Walks. - Marina Meila; Jianbo Shi (NIPS, 2000)

Tractable Bayesian Learning of Tree Belief Networks. - Marina Meila; Tommi S. Jaakkola (UAI, 2000)

Learning with Mixtures of Trees. - Marina Meila; Michael I. Jordan (J. Mach. Learn. Res., 2000)

A Random Walks View of Spectral Segmentation. - Marina Meila; Jianbo Shi (AISTATS, 2001)

A New Signature-Based Method for Efficient 3-D Object Recognition. - Salvador Ruiz-Correa; Linda G. Shapiro; Marina Meila (CVPR (1), 2001)

Intransitive Likelihood-Ratio Classifiers. - Jeff A. Bilmes; Gang Ji; Marina Meila (NIPS, 2001)

An Experimental Comparison of Model-Based Clustering Methods. - Marina Meila; David Heckerman (Mach. Learn., 2001)

Real-Time Particle Filters. - Cody C. T. Kwok; Dieter Fox; Marina Meila (NIPS, 2002)

Data centering in feature space. - Marina Meila (AISTATS, 2003)

Comparing Clusterings by the Variation of Information. - Marina Meila (COLT, 2003)

A New Paradigm for Recognizing 3-D Object Shapes from Range Data. - Salvador Ruiz-Correa; Linda G. Shapiro; Marina Meila (ICCV, 2003)

Adaptive real-time particle filters for robot localization. - Cody C. T. Kwok; Dieter Fox; Marina Meila (ICRA, 2003)

Discriminating Deformable Shape Classes. - Salvador Ruiz-Correa; Linda G. Shapiro; Marina Meila; Gabriel Berson (NIPS, 2003)

Spectral Clustering of Biological Sequence Data. - William Pentney; Marina Meila (AAAI, 2005)

Regularized spectral learning. - Marina Meila; Susan M. Shortreed; Liang Xu (AISTATS, 2005)

Comparing clusterings: an axiomatic view. - Marina Meila (ICML, 2005)

Unsupervised Spectral Learning. - Susan M. Shortreed; Marina Meila (UAI, 2005)

The uniqueness of a good optimum for K-means. - Marina Meila (ICML, 2006)

Symbolic Signatures for Deformable Shapes. - Salvador Ruiz-Correa; Linda G. Shapiro; Marina Meila; Gabriel Berson; Michael L. Cunningham; Raymond W. Sze (IEEE Trans. Pattern Anal. Mach. Intell., 2006)

Comparing Subspace Clusterings. - Anne Patrikainen; Marina Meila (IEEE Trans. Knowl. Data Eng., 2006)

Clustering by weighted cuts in directed graphs. - Marina Meila; William Pentney (SDM, 2007)

Consensus ranking under the exponential model. - Marina Meila; Kapil Phadnis; Arthur Patterson; Jeff A. Bilmes (UAI, 2007)

IκB, NF-κB Regulation Model: Simulation Analysis of Small Number of Molecules. - Anamika Sarkar; Marina Meila; B. Robert Franza (EURASIP J. Bioinform. Syst. Biol., 2007)

Preface. - Marina Meila; Xiaotong Shen (AISTATS, 2007)

Gravimetric Detection by Compressed Sensing. - Marina Meila; Caren Marzban; Ulvi Yurtsever (IGARSS (2), 2008)

Estimation and clustering with infinite rankings. - Marina Meila; Le Bao (UAI, 2008)

Tractable Search for Learning Exponential Models of Rankings. - Bhushan Mandhani; Marina Meila (AISTATS, 2009)

Building a Job Lanscape from Directional Transition Data. - Dominique C. Perrault-Joncas; Marina Meila; Marc Scott (AAAI Fall Symposium: Manifold Learning and Its Applications, 2010)

Dirichlet Process Mixtures of Generalized Mallows Models. - Marina Meila; Harr Chen (UAI, 2010)

Learning Bayesian Network Structure using LP Relaxations. - Tommi S. Jaakkola; David A. Sontag; Amir Globerson; Marina Meila (AISTATS, 2010)

An Exponential Model for Infinite Rankings. - Marina Meila; Le Bao (J. Mach. Learn. Res., 2010)

Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators. - Dominique C. Perrault-Joncas; Marina Meila (NIPS, 2011)

Local equivalences of distances between clusterings - a geometric perspective. - Marina Meila (Mach. Learn., 2012)

Experiments with Kemeny ranking: What works when? - Alnur Ali; Marina Meila (Math. Soc. Sci., 2012)

Consensus Ranking with Signed Permutations. - Raman Arora; Marina Meila (AISTATS, 2013)

Recursive Inversion Models for Permutations. - Christopher Meek; Marina Meila (NIPS, 2014)

Graph Sensitive Indices for Comparing Clusterings. - Zaeem Hussain; Marina Meila (CoRR, 2014)

Estimating Vector Fields on Manifolds and the Embedding of Directed Graphs. - Dominique C. Perrault-Joncas; Marina Meila (CoRR, 2014)

Improved graph Laplacian via geometric self-consistency. - Dominique C. Perrault-Joncas; Marina Meila (CoRR, 2014)

A class of network models recoverable by spectral clustering. - Yali Wan; Marina Meila (NIPS, 2015)

Benchmarking recovery theorems for the DC-SBM. - Yali Wan; Marina Meila (ISAIM, 2016)

Nearly Isometric Embedding by Relaxation. - James McQueen; Marina Meila; Dominique Joncas (NIPS, 2016)

Graph Clustering: Block-models and model free results. - Yali Wan; Marina Meila (NIPS, 2016)

megaman: Manifold Learning with Millions of points. - James McQueen; Marina Meila; Jacob VanderPlas; Zhongyue Zhang (CoRR, 2016)

Megaman: Scalable Manifold Learning in Python. - James McQueen; Marina Meila; Jacob VanderPlas; Zhongyue Zhang (J. Mach. Learn. Res., 2016)

Bayesian Non-Parametric Clustering of Ranking Data. - Marina Meila; Harr Chen (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Improved Graph Laplacian via Geometric Self-Consistency. - Dominique Joncas; Marina Meila; James McQueen (NIPS, 2017)

How to tell when a clustering is (approximately) correct using convex relaxations. - Marina Meila (NeurIPS, 2018)

How to sample connected K-partitions of a graph. - Marina Meila (CoRR, 2018)

A regression approach for explaining manifold embedding coordinates. - Marina Meila; Samson J. Koelle; Hanyu Zhang (CoRR, 2018)

Selecting the independent coordinates of manifolds with large aspect ratios. - Yu-Chia Chen; Marina Meila (NeurIPS, 2019)

Measuring the Robustness of Graph Properties. - Yali Wan; Marina Meila (CoRR, 2019)

Good (K-means) clusterings are unique (up to small perturbations). - Marina Meila (J. Multivar. Anal., 2019)

Guarantees for Hierarchical Clustering by the Sublevel Set method. - Marina Meila (CoRR, 2020)

The decomposition of the higher-order homology embedding constructed from the $k$-Laplacian. - Yu-Chia Chen; Marina Meila (NeurIPS, 2021)

Helmholtzian Eigenmap: Topological feature discovery & edge flow learning from point cloud data. - Yu-Chia Chen; Marina Meila; Ioannis G. Kevrekidis (CoRR, 2021)

Distribution free optimality intervals for clustering. - Marina Meila; Hanyu Zhang (CoRR, 2021)

To ArXiv or not to ArXiv: A Study Quantifying Pros and Cons of Posting Preprints Online. - Charvi Rastogi; Ivan Stelmakh; Xinwei Shen; Marina Meila; Federico Echenique; Shuchi Chawla 001; Nihar B. Shah (CoRR, 2022)

Manifold Coordinates with Physical Meaning. - Samson J. Koelle; Hanyu Zhang; Marina Meila; Yu-Chia Chen (J. Mach. Learn. Res., 2022)

Recursive inversion models for permutations. - Marina Meila; Annelise Wagner; Christopher Meek (Stat. Comput., 2022)

The Parametric Stability of Well-separated Spherical Gaussian Mixtures. - Hanyu Zhang; Marina Meila (CoRR, 2023)

Dictionary-based Manifold Learning. - Hanyu Zhang; Samson J. Koelle; Marina Meila (CoRR, 2023)

Manifold learning: what, how, and why. - Marina Meila; Hanyu Zhang (CoRR, 2023)

Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space. - Nikolaos Evangelou; Felix Dietrich; Eliodoro Chiavazzo; Daniel Lehmberg; Marina Meila; Ioannis G. Kevrekidis (J. Comput. Phys., 2023)

Consistency of Dictionary-Based Manifold Learning. - Samson J. Koelle; Hanyu Zhang; Octavian-Vlad Murad; Marina Meila (AISTATS, 2024)

Isometry pursuit. - Samson J. Koelle; Marina Meila (CoRR, 2024)

How well behaved is finite dimensional Diffusion Maps? - Wenyu Bo; Marina Meila (CoRR, 2024)

Piikun: an information theoretic toolkit for analysis and visualization of species delimitation metric space. - Jeet Sukumaran; Marina Meila (BMC Bioinform., 2024)

The Entropy and Crossentropy of Generalized Mallows Models. - Marina Meila (CoRR, 2025)

Cryo-em images are intrinsically low dimensional. - Luke Evans; Octavian-Vlad Murad; Lars Dingeldein; Pilar Cossio; Roberto Covino; Marina Meila (CoRR, 2025)