Guy Wolf

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Smita KrishnaswamyYale UniversityDirección de correo verificada de yale.edu
David van DijkAssistant Professor, Yale UniversityDirección de correo verificada de yale.edu
Kevin R. MoonUtah State UniversityDirección de correo verificada de usu.edu
Matthew HirnMichigan State UniversityDirección de correo verificada de msu.edu
Daniel B BurkhardtCellarity - Machine Learning ScientistDirección de correo verificada de cellarity.com
Amir AverbuchProfessor of Computer Science, Tel-Aviv UniversityDirección de correo verificada de math.tau.ac.il
Ronald Coifmanprofessor of mathematics yale universityDirección de correo verificada de math.yale.edu
Natalia IvanovaUniversity of GeorgiaDirección de correo verificada de uga.edu
Dana Pe'erSloan Kettering InstituteDirección de correo verificada de mskcc.org
Moshe SalhovComputer Science, Tel Aviv UniversityDirección de correo verificada de post.tau.ac.il
Stephane MallatProfesseur de Mathématiques Appliquées et Informatique, École Normale SupérieureDirección de correo verificada de ens.fr
Ofir LindenbaumAssistant Professor at Bar Ilan UniversityDirección de correo verificada de biu.ac.il
Yaniv ShmueliEngineering Manager, FacebookDirección de correo verificada de cs.tau.ac.il
Pekka NeittaanmäkiProfessor of Scientific Computing, University of JyväskyläDirección de correo verificada de jyu.fi
Aviv RotbartPhD student of Computer Science, Tel Aviv UniversityDirección de correo verificada de cs.tau.ac.il
Gil DavidUniversity of JyvaskylaDirección de correo verificada de jyu.fi
Scott GiganteSenior Machine Learning Scientist, Immunai

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Guy Wolf

Université de Montréal

Dirección de correo verificada de umontreal.ca - Página principal

Exploratory Data Analysis Dimensionality Reduction Manifold Learning Geometric Deep Learning Graph Signal Processing


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Recovering gene interactions from single-cell data using data diffusion D Van Dijk, R Sharma, J Nainys, K Yim, P Kathail, AJ Carr, C Burdziak, ... Cell 174 (3), 716-729. e27, 2018	844*	2018
Visualizing structure and transitions in high-dimensional biological data KR Moon, D van Dijk, Z Wang, S Gigante, DB Burkhardt, WS Chen, K Yim, ... Nature biotechnology 37 (12), 1482-1492, 2019	396*	2019
Exploring single-cell data with deep multitasking neural networks M Amodio, D van Dijk, K Srinivasan, WS Chen, H Mohsen, KR Moon, ... Nature Methods 16, 1139–1145, 2019	149	2019
Manifold learning-based methods for analyzing single-cell RNA-sequencing data KR Moon, JS Stanley III, D Burkhardt, D van Dijk, G Wolf, S Krishnaswamy Current Opinion in Systems Biology 7, 36-46, 2018	83	2018
Geometric scattering for graph data analysis F Gao, G Wolf, M Hirn Proceedings of the 36th International Conference on Machine Learning, PMLR …, 2019	59	2019
Quantifying the effect of experimental perturbations at single-cell resolution DB Burkhardt, JS Stanley, A Tong, AL Perdigoto, SA Gigante, KC Herold, ... Nature Biotechnology 39 (5), 619-629, 2021	51*	2021
Scattering GCN: Overcoming oversmoothness in graph convolutional networks Y Min, F Wenkel, G Wolf Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020	41	2020
Trajectorynet: A dynamic optimal transport network for modeling cellular dynamics A Tong, J Huang, G Wolf, D Van Dijk, S Krishnaswamy International Conference on Machine Learning, 9526-9536, 2020	27	2020
Structural and developmental principles of neuropil assembly in C. elegans MW Moyle, KM Barnes, M Kuchroo, A Gonopolskiy, LH Duncan, ... Nature 591 (7848), 99-104, 2021	22	2021
Geometry-based data generation O Lindenbaum, JS Stanley III, G Wolf, S Krishnaswamy Advances in Neural Information Processing Systems 31 (NeurIPS 2018), 2018	22	2018
Uncovering axes of variation among single-cell cancer specimens WS Chen, N Zivanovic, D van Dijk, G Wolf, B Bodenmiller, ... Nature methods 17 (3), 302-310, 2020	20	2020
Approximately-isometric diffusion maps M Salhov, A Bermanis, G Wolf, A Averbuch Applied and Computational Harmonic Analysis 38 (3), 399-419, 2015	18	2015
Fixing bias in reconstruction-based anomaly detection with lipschitz discriminators A Tong, G Wolf, S Krishnaswamy 2020 IEEE 30th International Workshop on Machine Learning for Signal …, 2020	16*	2020
Uncovering the topology of time-varying fMRI data using cubical persistence B Rieck, T Yates, C Bock, K Borgwardt, G Wolf, N Turk-Browne, ... Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020	15	2020
Diffusion-based kernel methods on Euclidean metric measure spaces A Bermanis, G Wolf, A Averbuch Applied and Computational Harmonic Analysis 41 (1), 190-213, 2016	15	2016
Rigid motion model for audio source separation G Wolf, S Mallat, S Shamma IEEE Transactions on Signal Processing 64 (7), 1822-1831, 2015	15	2015
Patch-to-tensor embedding M Salhov, G Wolf, A Averbuch Applied and Computational Harmonic Analysis, 2011	14	2011
Cover-based bounds on the numerical rank of Gaussian kernels A Bermanis, G Wolf, A Averbuch Applied and Computational Harmonic Analysis 36 (2), 302-315, 2014	13	2014
Linear-projection diffusion on smooth Euclidean submanifolds G Wolf, A Averbuch Applied and Computational Harmonic Analysis 34 (1), 1-14, 2013	13	2013
Updating kernel methods in spectral decomposition by affinity perturbations Y Shmueli, G Wolf, A Averbuch Linear algebra and its applications 437 (6), 1356-1365, 2012	12	2012

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