2021-11
Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators
MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data.
2021-10
Towards a Taxonomy of Graph Learning Datasets.
Data-Driven Learning of Geometric Scattering Modules for GNNs
Multimodal Data Visualization and Denoising with Integrated Diffusion
Hierarchical Graph Neural Nets can Capture Long-Range Interactions
2021-09
Data-driven approaches for genetic characterization of SARS-CoV-2 lineages
Topological Analysis of Single-Cell Hierarchy Reveals Inflammatory Glial Landscape of Macular Degeneration
2021-07
Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance.
Parametric Scattering Networks.
Diffusion Earth Mover's Distance and Distribution Embeddings
Random Forest-Based Diffusion Information Geometry for Supervised Visualization and Data Exploration
2021-06
Geometric Scattering Attention Networks
Genomic epidemiology and associated clinical outcomes of a SARS-CoV-2 outbreak in a general adult hospital in Quebec
2021-05
Decoupled Greedy Learning of Graph Neural Networks
Visualizing High-Dimensional Trajectories on the Loss-Landscape of ANNs
Data-driven Learning of Geometric Scattering Networks
2021-02
Structural and developmental principles of neuropil assembly in C. elegans
Multimodal data visualization, denoising and clustering with integrated diffusion.
Quantifying the effect of experimental perturbations at single-cell resolution.
2021-01
Topological analysis of single-cell data reveals shared glial landscape of macular degeneration and neurodegenerative diseases
2020-12
Uncovering the Folding Landscape of RNA Secondary Structure Using Deep Graph Embeddings
Extendable and invertible manifold learning with geometry regularized autoencoders
Extendable and invertible manifold learning with geometry regularized autoencoders
2020-11
Multiscale PHATE Exploration of SARS-CoV-2 Data Reveals Multimodal Signatures of Disease
Multiscale PHATE Exploration of SARS-CoV-2 Data Reveals Multimodal Signatures of Disease
2020-10
Learning General Transformations of Data for Out-of-Sample Extensions
2020-09
Fixing Bias in Reconstruction-Based Anomaly Detection with Lipschitz Discriminators
2020-08
Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds.
2020-07
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds.
2020-06
Advantages of biologically-inspired adaptive neural activation in RNNs during learning.
Supervised Visualization for Data Exploration
Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings
2020-05
Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks
2020-04
Interpretable Neuron Structuring with Graph Spectral Regularization.
2020-03
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks
2020-02
Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming
2020-01
Uncovering axes of variation among single-cell cancer specimens.
Internal representation dynamics and geometry in recurrent neural networks.
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence
Author Correction: Visualizing structure and transitions in high-dimensional biological data.
2019-12
Finding Archetypal Spaces Using Neural Networks
Visualizing structure and transitions in high-dimensional biological data
2019-11
Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms
2019-10
Exploring single-cell data with deep multitasking neural networks.
2019-09
Beyond GANs: Transforming without a Target Distribution
Geometric wavelet scattering on graphs and manifolds
Quantifying the effect of experimental perturbations in single-cell RNA-sequencing data using graph signal processing
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