Gal Mishne

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 53

Top Topics

Graph Laplacian

Top Venues

Publications

Jiancheng Xie, Lou C. Kohler Voinov, Noga Mudrik, Gal Mishne, Adam S. Charles
Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training. CoRR (2024)
Changhao Shi, Gal Mishne
Learning Cartesian Product Graphs with Laplacian Constraints. CoRR (2024)
Changhao Shi, Gal Mishne
Learning Cartesian Product Graphs with Laplacian Constraints. AISTATS (2024)
Mitchell Black, Zhengchao Wan, Gal Mishne, Amir Nayyeri, Yusu Wang
Comparing Graph Transformers via Positional Encodings. CoRR (2024)
Gal Mishne, Adam S. Charles
Deep and shallow data science for multi-scale optical neuroscience. CoRR (2024)
Xinyue Xia, Gal Mishne, Yusu Wang
Implicit Graphon Neural Representation. AISTATS (2023)
Alexander Cloninger, Gal Mishne, Andreas Oslandsbotn, Sawyer Jack Robertson, Zhengchao Wan, Yusu Wang
Random Walks, Conductance, and Resistance for the Connection Graph Laplacian. CoRR (2023)
Changhao Shi, Gal Mishne
Graph Laplacian Learning with Exponential Family Noise. CoRR (2023)
Gal Mishne, Zhengchao Wan, Yusu Wang, Sheng Yang
The Numerical Stability of Hyperbolic Representation Learning. ICML (2023)
Sawyer Jack Robertson, Dhruv Kohli, Gal Mishne, Alexander Cloninger
On a Generalization of Wasserstein Distance and the Beckmann Problem to Connection Graphs. CoRR (2023)
Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning. CoRR (2023)
Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning. ICML (2023)
Dhruv Kohli, Gal Mishne, Alexander Cloninger
Local Rigidity of Patch Framework Realization. CoRR (2023)
Chester Holtz, Pengwen Chen, Alexander Cloninger, Chung-Kuan Cheng, Gal Mishne
Semi-Supervised Laplacian Learning on Stiefel Manifolds. CoRR (2023)
Noga Mudrik, Gal Mishne, Adam S. Charles
SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States. CoRR (2023)
Ram Dyuthi Sristi, Ofir Lindenbaum, Maria Lavzin, Jackie Schiller, Gal Mishne, Hadas Benisty
Contextual Feature Selection with Conditional Stochastic Gates. CoRR (2023)
Jesse He, Tristan Brugère, Gal Mishne
Product Manifold Learning with Independent Coordinate Selection. TAG-ML (2023)
George Armstrong, Gibraan Rahman, Cameron Martino, Daniel McDonald, Antonio Gonzalez, Gal Mishne, Rob Knight
Applications and Comparison of Dimensionality Reduction Methods for Microbiome Data. Frontiers Bioinform. 2 (2022)
Sristi Ram Dyuthi, Gal Mishne, Ariel Jaffe
DiSC: Differential Spectral Clustering of Features. CoRR (2022)
Min Zhang, Gal Mishne, Eric C. Chi
Multi-scale affinities with missing data: Estimation and applications. Stat. Anal. Data Min. 15 (3) (2022)
Adam S. Charles, Nathan Cermak, Rifqi O. Affan, Benjamin B. Scott, Jackie Schiller, Gal Mishne
GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging. IEEE Trans. Image Process. 31 (2022)
Chester Holtz, Tsui-Wei Weng, Gal Mishne
Learning Sample Reweighting for Accuracy and Adversarial Robustness. CoRR (2022)
Sristi Ram Dyuthi, Gal Mishne, Ariel Jaffe
DiSC: Differential Spectral Clustering of Features. NeurIPS (2022)
Chester Holtz, Gal Mishne, Alexander Cloninger
Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors. CoRR (2022)
Gal Mishne, Zhengchao Wan, Yusu Wang, Sheng Yang
The Numerical Stability of Hyperbolic Representation Learning. CoRR (2022)
Chester Holtz, Gal Mishne, Alexander Cloninger
Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors. TAG-ML (2022)
Xinyue Xia, Gal Mishne, Yusu Wang
Implicit Graphon Neural Representation. CoRR (2022)
Siyuan Gao, Xinyue Xia, Dustin Scheinost, Gal Mishne
Smooth graph learning for functional connectivity estimation. NeuroImage 239 (2021)
Dhruv Kohli, Alexander Cloninger, Gal Mishne
LDLE: Low Distortion Local Eigenmaps. J. Mach. Learn. Res. 22 (2021)
Dhruv Kohli, Alexander Cloninger, Gal Mishne
LDLE: Low Distortion Local Eigenmaps. CoRR (2021)
Changhao Shi, Chester Holtz, Gal Mishne
Online Adversarial Purification based on Self-supervised Learning. ICLR (2021)
Changhao Shi, Sivan Schwartz, Shahar Levy, Shay Achvat, Maisan Abboud, Amir Ghanayim, Jackie Schiller, Gal Mishne
Learning Disentangled Behavior Embeddings. NeurIPS (2021)
Haidong Yi, Le Huang, Gal Mishne, Eric C. Chi
COBRAC: a fast implementation of convex biclustering with compression. Bioinform. 37 (20) (2021)
Changhao Shi, Chester Holtz, Gal Mishne
Online Adversarial Purification based on Self-Supervision. CoRR (2021)
Jay S. Stanley III, Eric C. Chi, Gal Mishne
Multiway Graph Signal Processing on Tensors: Integrative Analysis of Irregular Geometries. IEEE Signal Process. Mag. 37 (6) (2020)
Ofir Lindenbaum, Amir Sagiv, Gal Mishne, Ronen Talmon
Kernel-based parameter estimation of dynamical systems with unknown observation functions. CoRR (2020)
Jay S. Stanley III, Eric C. Chi, Gal Mishne
Multi-way Graph Signal Processing on Tensors: Integrative analysis of irregular geometries. CoRR (2020)
Ariel Jaffe, Yuval Kluger, George C. Linderman, Gal Mishne, Stefan Steinerberger
Randomized near-neighbor graphs, giant components and applications in data science. J. Appl. Probab. 57 (2) (2020)
Siyuan Gao, Gal Mishne, Dustin Scheinost
Poincaré Embedding Reveals Edge-Based Functional Networks of the Brain. MICCAI (7) (2020)
Xiuyuan Cheng, Gal Mishne
Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph Laplacian. SIAM J. Imaging Sci. 13 (2) (2020)
Scott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal Mishne
Visualizing the PHATE of Neural Networks. CoRR (2019)
Gal Mishne, Eric C. Chi, Ronald R. Coifman
Co-manifold learning with missing data. ICML (2019)
Gal Mishne, Adam S. Charles
Learning Spatially-correlated Temporal Dictionaries for Calcium Imaging. ICASSP (2019)
Scott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal Mishne
Visualizing the PHATE of Neural Networks. NeurIPS (2019)
Siyuan Gao, Gal Mishne, Dustin Scheinost
A Hierarchical Manifold Learning Framework for High-Dimensional Neuroimaging Data. IPMI (2019)
Xiuyuan Cheng, Gal Mishne
Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph Laplacian. CoRR (2018)
Gal Mishne, Eric C. Chi, Ronald R. Coifman
Co-manifold learning with missing data. CoRR (2018)
Gal Mishne, Ronen Talmon, Israel Cohen, Ronald R. Coifman, Yuval Kluger
Data-Driven Tree Transforms and Metrics. IEEE Trans. Signal Inf. Process. over Networks 4 (3) (2018)
Gal Mishne, Ronen Talmon, Israel Cohen, Ronald R. Coifman, Yuval Kluger
Data-Driven Tree Transforms and Metrics. CoRR (2017)
Gal Mishne, Israel Cohen
Iterative diffusion-based anomaly detection. ICASSP (2017)
George C. Linderman, Gal Mishne, Yuval Kluger, Stefan Steinerberger
Randomized Near Neighbor Graphs, Giant Components, and Applications in Data Science. CoRR (2017)
Ron Amit, Gal Mishne, Ronen Talmon
Improving resolution in supervised patch-based target detection. ICASSP (2016)
Gal Mishne, Ronen Talmon, Ron Meir, Jackie Schiller, Maria Lavzin, Uri Dubin, Ronald R. Coifman
Hierarchical Coupled-Geometry Analysis for Neuronal Structure and Activity Pattern Discovery. IEEE J. Sel. Top. Signal Process. 10 (7) (2016)
Gal Mishne, Ronen Talmon, Israel Cohen
Graph-Based Supervised Automatic Target Detection. IEEE Trans. Geosci. Remote. Sens. 53 (5) (2015)
Gal Mishne, Uri Shaham, Alexander Cloninger, Israel Cohen
Diffusion Nets. CoRR (2015)
Gal Mishne, Israel Cohen
Multiscale anomaly detection using diffusion maps and saliency score. ICASSP (2014)
Gal Mishne, Israel Cohen
Multiscale Anomaly Detection Using Diffusion Maps. IEEE J. Sel. Top. Signal Process. 7 (1) (2013)