Henry Kvinge - RankMe

87 papers A* 6C 3Journal 52Unranked 23

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Can Neural Networks Learn Small Algebraic Worlds? An Investigation Into the Group-theoretic Structures Learned By Narrow Models Trained To Predict Group Operations. CoRR Henry Kvinge, Andrew Aguilar, Nayda Farnsworth, Grace O'Brien, Robert Jasper, Sarah Scullen, Helen Jenne
2026	J	`jnl`	Generalist multimodal AI: A review of architectures, challenges and opportunities. Neurocomputing Sai Munikoti, Ian Stewart, Sameera Horawalavithana, Henry Kvinge, Tegan Emerson, Sandra E. Thompson, Karl Pazdernik
2026	J	`jnl`	MINAR: Mechanistic Interpretability for Neural Algorithmic Reasoning. CoRR Jesse He, Helen Jenne, Max Vargas, Davis Brown, Gal Mishne, Yusu Wang, Henry Kvinge
2026	J	`jnl`	What do Geometric Hallucination Detection Metrics Actually Measure? CoRR Eric Yeats, John Buckheit, Sarah Scullen, Brendan Kennedy, Loc Truong, Davis Brown, Bill Kay, Cliff A. Joslyn, Tegan Emerson, Michael J. Henry, John Emanuello, Henry Kvinge
2025	J	`jnl`	A Connection Between Score Matching and Local Intrinsic Dimension. CoRR Eric Yeats, Aaron Jacobson, Darryl Hannan, Yiran Jia, Timothy Doster, Henry Kvinge, Scott Mahan
2025	J	`jnl`	Automating Evaluation of Diffusion Model Unlearning with (Vision-) Language Model World Knowledge. CoRR Eric Yeats, Darryl Hannan, Henry Kvinge, Timothy Doster, Scott Mahan
2025	J	`jnl`	Even with AI, Bijection Discovery is Still Hard: The Opportunities and Challenges of OpenEvolve for Novel Bijection Construction. CoRR Davis Brown, Jesse He, Helen Jenne, Henry Kvinge, Max Vargas
2025	J	`jnl`	FMG-Det: Foundation Model Guided Robust Object Detection. CoRR Darryl Hannan, Timothy Doster, Henry Kvinge, Adam Attarian, Yijing Watkins
2025	—	`conf`	Foundation Models for Remote Sensing: An Analysis of MLLMs for Object Localization. CVPR Workshops Darryl Hannan, John Cooper, Dylan White, Timothy Doster, Henry Kvinge, Yijing Watkins
2025	J	`jnl`	Foundation Models for Remote Sensing: An Analysis of MLLMs for Object Localization. CoRR Darryl Hannan, John Cooper, Dylan White, Timothy Doster, Henry Kvinge, Yijing Watkins
2025	A*	`conf`	Machine Learning meets Algebraic Combinatorics: A Suite of Datasets Capturing Research-level Conjecturing Ability in Pure Mathematics. ICML Herman Chau, Helen Jenne, Davis Brown, Jesse He, Mark Raugas, Sara C. Billey, Henry Kvinge
2025	J	`jnl`	Machine Learning meets Algebraic Combinatorics: A Suite of Datasets Capturing Research-level Conjecturing Ability in Pure Mathematics. CoRR Herman Chau, Helen Jenne, Davis Brown, Jesse He, Mark Raugas, Sara C. Billey, Henry Kvinge
2025	A*	`conf`	Machines and Mathematical Mutations: Using GNNs to Characterize Quiver Mutation Classes. ICML Jesse He, Helen Jenne, Herman Chau, Davis Brown, Mark Raugas, Sara C. Billey, Henry Kvinge
2025	J	`jnl`	Saddle-Free Guidance: Improved On-Manifold Sampling without Labels or Additional Training. CoRR Eric Yeats, Darryl Hannan, Wilson Fearn, Timothy Doster, Henry Kvinge, Scott Mahan
2024	J	`jnl`	Generalist Multimodal AI: A Review of Architectures, Challenges and Opportunities. CoRR Sai Munikoti, Ian Stewart, Sameera Horawalavithana, Henry Kvinge, Tegan Emerson, Sandra E. Thompson, Karl Pazdernik
2024	—	`conf`	ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain. GRaM Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol-Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Meznar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frédéric Wantiez, Alexander Weers, Patrik Zajec, Blaz Skrlj, Nina Miolane
2024	J	`jnl`	ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain. CoRR Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol-Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree P. Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Meznar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frédéric Wantiez, Alexander Weers, Patrik Zajec, Blaz Skrlj, Nina Miolane
2024	—	`conf`	Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss. GRaM Sylvia Howland, Keerti Sahithi Kappagantula, Henry Kvinge, Tegan Emerson
2024	J	`jnl`	Machines and Mathematical Mutations: Using GNNs to Characterize Quiver Mutation Classes. CoRR Jesse He, Helen Jenne, Herman Chau, Davis Brown, Mark Raugas, Sara C. Billey, Henry Kvinge
2024	J	`jnl`	Model editing for distribution shifts in uranium oxide morphological analysis. CoRR Davis Brown, Cody Nizinski, Madelyn Shapiro, Corey Fallon, Tianzhixi Yin, Henry Kvinge, Jonathan H. Tu
2024	—	`conf`	Preface to Geometry-grounded Representation Learning and Generative Modeling (GRaM) Workshop. GRaM Sharvaree Vadgama, Erik J. Bekkers, Alison Pouplin, Sékou-Oumar Kaba, Robin Walters, Hannah Lawrence, Tegan Emerson, Henry Kvinge, Jakub M. Tomczak, Stefanie Jegelka
2024	—	`ed.`	Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at ICML 2024, 29 July 2024, Vienna, Austria GRaM Sharvaree Vadgama, Erik J. Bekkers, Alison Pouplin, Sékou-Oumar Kaba, Robin Walters, Hannah Lawrence, Tegan Emerson, Henry Kvinge, Jakub M. Tomczak, Stefanie Jegelka
2023	J	`jnl`	Attributing Learned Concepts in Neural Networks to Training Data. CoRR Nicholas Konz, Charles Godfrey, Madelyn Shapiro, Jonathan H. Tu, Henry Kvinge, Davis Brown
2023	J	`jnl`	ColMix - A Simple Data Augmentation Framework to Improve Object Detector Performance and Robustness in Aerial Images. CoRR Cuong Ly, Grayson Jorgenson, Dan Rosa de Jesus, Henry Kvinge, Adam Attarian, Yijing Watkins
2023	J	`jnl`	Exploring the Representation Manifolds of Stable Diffusion Through the Lens of Intrinsic Dimension. CoRR Henry Kvinge, Davis Brown, Charles Godfrey
2023	J	`jnl`	Fast computation of permutation equivariant layers with the partition algebra. CoRR Charles Godfrey, Michael G. Rawson, Davis Brown, Henry Kvinge
2023	J	`jnl`	Haldane Bundles: A Dataset for Learning to Predict the Chern Number of Line Bundles on the Torus. CoRR Cody Tipton, Elizabeth Coda, Davis Brown, Alyson Bittner, Jung H. Lee, Grayson Jorgenson, Tegan Emerson, Henry Kvinge
2023	—	`conf`	Haldane bundles: a dataset for learning to predict the Chern number of line bundles on the torus. NeurReps Cody Tipton, Elizabeth Coda, Davis Brown, Alyson Bittner, Jung Lee, Grayson Jorgenson, Tegan Emerson, Henry Kvinge
2023	—	`conf`	How many dimensions are required to find an adversarial example? CVPR Workshops Charles Godfrey, Henry Kvinge, Elise Bishoff, Myles Mckay, Davis Brown, Tim Doster, Eleanor Byler
2023	J	`jnl`	How many dimensions are required to find an adversarial example? CoRR Charles Godfrey, Henry Kvinge, Elise Bishoff, Myles Mckay, Davis Brown, Tim Doster, Eleanor Byler
2023	J	`jnl`	ICML 2023 Topological Deep Learning Challenge : Design and Results. CoRR Mathilde Papillon, Mustafa Hajij, Florian Frantzen, Josef Hoppe, Helen Jenne, Johan Mathe, Audun Myers, Theodore Papamarkou, Michael T. Schaub, Ghada Zamzmi, Tolga Birdal, Tamal K. Dey, Tim Doster, Tegan Emerson, Gurusankar Gopalakrishnan, Devendra Govil, Vincent P. Grande, Aldo Guzmán-Sáenz, Henry Kvinge, Neal Livesay, Jan Meissner, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Maneel Reddy Karri, Paul Rosen, Sophia Sanborn, Michael Scholkemper, Robin Walters, Jens Agerberg, Georg Bökman, Sadrodin Barikbin, Claudio Battiloro, Gleb Bazhenov, Guillermo Bernárdez, Aiden Brent, Sergio Escalera, Simone Fiorellino, Dmitrii Gavrilev, Mohammed Hassanin, Paul Häusner, Odin Hoff Gardaa, Abdelwahed Khamis, Manuel Lecha, German Magai, Tatiana Malygina, Pavlo Melnyk, et al.
2023	—	`conf`	ICML 2023 Topological Deep Learning Challenge: Design and Results. TAG-ML Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane
2023	—	`conf`	Internal representations of vision models through the lens of frames on data manifolds. NeurReps Henry Kvinge, Grayson Jorgenson, Davis Brown, Charles Godfrey, Tegan Emerson
2023	—	`conf`	Making Corgis Important for Honeycomb Classification: Adversarial Attacks on Concept-based Explainability Tools. CVPR Workshops Davis Brown, Henry Kvinge
2023	J	`jnl`	Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Towards ML-assisted Advanced Manufacturing. CoRR Scott Howland, Lara Kassab, Keerti Kappagantula, Henry Kvinge, Tegan Emerson
2023	—	`conf`	Preface. TAG-ML Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
2023	J	`jnl`	Robustness of edited neural networks. CoRR Davis Brown, Charles Godfrey, Cody Nizinski, Jonathan H. Tu, Henry Kvinge
2023	J	`jnl`	SCITUNE: Aligning Large Language Models with Scientific Multimodal Instructions. CoRR Sameera Horawalavithana, Sai Munikoti, Ian Stewart, Henry Kvinge
2023	—	`conf`	TopFusion: Using Topological Feature Space for Fusion and Imputation in Multi-Modal Data. CVPR Workshops Audun Myers, Henry Kvinge, Tegan Emerson
2023	—	`ed.`	Topological, Algebraic and Geometric Learning Workshops 2023, 28 July 2023, Honolulu, HI, USA TAG-ML Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
2023	J	`jnl`	Understanding the Inner Workings of Language Models Through Representation Dissimilarity. CoRR Davis Brown, Charles Godfrey, Nicholas Konz, Jonathan H. Tu, Henry Kvinge
2023	A*	`conf`	Understanding the Inner-workings of Language Models Through Representation Dissimilarity. EMNLP Davis Brown, Charles Godfrey, Nicholas Konz, Jonathan H. Tu, Henry Kvinge
2022	A*	`conf`	Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps. ICLR Nico Courts, Henry Kvinge
2022	J	`jnl`	Convolutional networks inherit frequency sensitivity from image statistics. CoRR Charles Godfrey, Elise Bishoff, Myles Mckay, Davis Brown, Grayson Jorgenson, Henry Kvinge, Eleanor Byler
2022	J	`jnl`	Do Neural Networks Trained with Topological Features Learn Different Internal Representations? CoRR Sarah McGuire, Shane Jackson, Tegan Emerson, Henry Kvinge
2022	—	`conf`	Do neural networks trained with topological features learn different internal representations? NeurReps Sarah McGuire, Shane Jackson, Tegan Emerson, Henry Kvinge
2022	—	`conf`	Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps. TAG-ML Elizabeth Coda, Nico Courts, Colby Wight, Loc Truong, WoongJo Choi, Charles Godfrey, Tegan Emerson, Keerti Kappagantula, Henry Kvinge
2022	J	`jnl`	Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps. CoRR Elizabeth Coda, Nico Courts, Colby Wight, Loc Truong, WoongJo Choi, Charles Godfrey, Tegan Emerson, Keerti Kappagantula, Henry Kvinge
2022	A*	`conf`	In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? NeurIPS Henry Kvinge, Tegan Emerson, Grayson Jorgenson, Scott Vasquez, Tim Doster, Jesse D. Lew
2022	J	`jnl`	In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? CoRR Henry Kvinge, Tegan H. Emerson, Grayson Jorgenson, Scott Vasquez, Timothy Doster, Jesse D. Lew
2022	J	`jnl`	Neural frames: A Tool for Studying the Tangent Bundles Underlying Image Datasets and How Deep Learning Models Process Them. CoRR Henry Kvinge, Grayson Jorgenson, Davis Brown, Charles Godfrey, Tegan Emerson
2022	A*	`conf`	On the Symmetries of Deep Learning Models and their Internal Representations. NeurIPS Charles Godfrey, Davis Brown, Tegan Emerson, Henry Kvinge
2022	J	`jnl`	On the Symmetries of Deep Learning Models and their Internal Representations. CoRR Charles Godfrey, Davis Brown, Tegan Emerson, Henry Kvinge
2022	—	`conf`	Preface. TAG-ML Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf
2022	—	`conf`	Random Filters for Enriching the Discriminatory power of Topological Representations. TAG-ML Grayson Jorgenson, Henry Kvinge, Tegan Emerson, Colin C. Olson
2022	—	`conf`	TopTemp: Parsing Precipitate Structure from Temper Topology. TAG-ML Lara Kassab, Scott Howland, Henry Kvinge, Keerti Sahithi Kappagantula, Tegan Emerson
2022	J	`jnl`	TopTemp: Parsing Precipitate Structure from Temper Topology. CoRR Lara Kassab, Scott Howland, Henry Kvinge, Keerti Sahithi Kappagantula, Tegan Emerson
2022	—	`ed.`	Topological, Algebraic and Geometric Learning Workshops 2022, 25-22 July 2022, Virtual TAG-ML Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf
2021	J	`jnl`	A Topological-Framework to Improve Analysis of Machine Learning Model Performance. CoRR Henry Kvinge, Colby Wight, Sarah Akers, Scott Howland, WoongJo Choi, Xiaolong Ma, Luke J. Gosink, Elizabeth Jurrus, Keerti Kappagantula, Tegan H. Emerson
2021	J	`jnl`	Brittle interpretations: The Vulnerability of TCAV and Other Concept-based Explainability Tools to Adversarial Attack. CoRR Davis Brown, Henry Kvinge
2021	J	`jnl`	Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps. CoRR Nico Courts, Henry Kvinge
2021	J	`jnl`	DNA: Dynamic Network Augmentation. CoRR Scott Mahan, Tim Doster, Henry Kvinge
2021	J	`jnl`	Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing. CoRR Loc Truong, WoongJo Choi, Colby Wight, Lizzy Coda, Tegan Emerson, Keerti Kappagantula, Henry Kvinge
2021	—	`conf`	Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning. MetaDL@AAAI Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas
2021	J	`jnl`	Hypergraph models of biological networks to identify genes critical to pathogenic viral response. BMC Bioinform. Song Feng, Emily Heath, Brett A. Jefferson, Cliff A. Joslyn, Henry Kvinge, Hugh D. Mitchell, Brenda Praggastis, Amie J. Eisfeld, Amy C. Sims, Larissa B. Thackray, Shufang Fan, Kevin B. Walters, Peter J. Halfmann, Danielle Westhoff-Smith, Qing Tan, Vineet D. Menachery, Timothy P. Sheahan, Adam S. Cockrell, Jacob F. Kocher, Kelly G. Stratton, Natalie C. Heller, Lisa M. Bramer, Michael S. Diamond, Ralph S. Baric, Katrina M. Waters, Yoshihiro Kawaoka, Jason E. McDermott, Emilie Purvine
2021	—	`conf`	Multi-Dimensional Scaling on Groups. ICCVW Mark Blumstein, Henry Kvinge
2021	J	`jnl`	One Representation to Rule Them All: Identifying Out-of-Support Examples in Few-shot Learning with Generic Representations. CoRR Henry Kvinge, Scott Howland, Nico Courts, Lauren A. Phillips, John Buckheit, Zachary New, Elliott Skomski, Jung H. Lee, Sandeep Tiwari, Jessica Hibler, Courtney D. Corley, Nathan O. Hodas
2021	J	`jnl`	Prototypical Region Proposal Networks for Few-Shot Localization and Classification. CoRR Elliott Skomski, Aaron Tuor, Andrew Avila, Lauren A. Phillips, Zachary New, Henry Kvinge, Courtney D. Corley, Nathan O. Hodas
2021	J	`jnl`	Rotating spiders and reflecting dogs: a class conditional approach to learning data augmentation distributions. CoRR Scott Mahan, Henry Kvinge, Tim Doster
2021	—	`conf`	Sheaves as a Framework for Understanding and Interpreting Model Fit. ICCVW Henry Kvinge, Brett A. Jefferson, Cliff A. Joslyn, Emilie Purvine
2021	J	`jnl`	Sheaves as a Framework for Understanding and Interpreting Model Fit. CoRR Henry Kvinge, Brett A. Jefferson, Cliff A. Joslyn, Emilie Purvine
2020	J	`jnl`	Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning. CoRR Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas
2020	C	`conf`	Rotational Equivariance for Object Classification Using xView. IGARSS Lucius Bynum, Timothy Doster, Tegan H. Emerson, Henry Kvinge
2019	—	`conf`	A Walk Through Spectral Bands: Using Virtual Reality to Better Visualize Hyperspectral Data. WSOM+ Henry Kvinge, Michael Kirby, Chris Peterson, Chad Eitel, Tod Clapp
2019	J	`jnl`	A data-driven approach to sampling matrix selection for compressive sensing. CoRR Elin Farnell, Henry Kvinge, John P. Dixon, Julia R. Dupuis, Michael Kirby, Chris Peterson, Elizabeth C. Schundler, Christian W. Smith
2019	J	`jnl`	More chemical detection through less sampling: amplifying chemical signals in hyperspectral data cubes through compressive sensing. CoRR Henry Kvinge, Elin Farnell, Julia R. Dupuis, Michael Kirby, Chris Peterson, Elizabeth C. Schundler
2019	C	`conf`	Rare Geometries: Revealing Rare Categories via Dimension-Driven Statistics. ICMLA Henry Kvinge, Elin Farnell, Jingya Li, Yujia Chen
2019	J	`jnl`	Rare geometries: revealing rare categories via dimension-driven statistics. CoRR Henry Kvinge, Elin Farnell
2018	C	`conf`	A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction. ISPDC Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson
2018	J	`jnl`	A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction. CoRR Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson
2018	—	`conf`	Endmember Extraction on the Grassmannian. DSW Elin Farnell, Henry Kvinge, Michael Kirby, Chris Peterson
2018	J	`jnl`	Endmember Extraction on the Grassmannian. CoRR Elin Farnell, Henry Kvinge, Michael Kirby, Chris Peterson
2018	J	`jnl`	Letting symmetry guide visualization: multidimensional scaling on groups. CoRR Henry Kvinge, Mark Blumstein
2018	J	`jnl`	Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large data sets. CoRR Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson
2018	—	`conf`	Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large datasets. IEEE BigData Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson
2018	—	`conf`	Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets. HPEC Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson
2018	J	`jnl`	Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets. CoRR Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson