4 citations · 9 across the 9 of their papers we have counts for
13 papers
DiSC: Differential Spectral Clustering of Features
Ram Dyuthi Sristi, Gal Mishne, Ariel Jaffe
Selecting subsets of features that differentiate between two conditions is a key task in a broad range of scientific domains. In many applications, the features of interest form cl…
Learning Sample Reweighting for Accuracy and Adversarial Robustness
Chester Holtz, Tsui-Wei Weng, Gal Mishne
There has been great interest in enhancing the robustness of neural network classifiers to defend against adversarial perturbations through adversarial training, while balancing th…
Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors
Chester Holtz, Gal Mishne, Alexander Cloninger
Probabilistic generative models provide a flexible and systematic framework for learning the underlying geometry of data. However, model selection in this setting is challenging, p…
Data Processing of Functional Optical Microscopy for Neuroscience
Hadas Benisty, Alexander Song, Gal Mishne +1
Functional optical imaging in neuroscience is rapidly growing with the development of new optical systems and fluorescence indicators. To realize the potential of these massive spa…
Multi-way Graph Signal Processing on Tensors: Integrative analysis of irregular geometries
Jay S. Stanley, Eric C. Chi, Gal Mishne
Graph signal processing (GSP) is an important methodology for studying data residing on irregular structures. As acquired data is increasingly taking the form of multi-way tensors,…
Visualizing the PHATE of Neural Networks
Scott Gigante, Adam S. Charles, Smita Krishnaswamy +1
Understanding why and how certain neural networks outperform others is key to guiding future development of network architectures and optimization methods. To this end, we introduc…