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07/08/2023
Manifold Filter-Combine Networks
We introduce a class of manifold neural networks (MNNs) that we call Man...
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06/13/2023
Inferring dynamic regulatory interaction graphs from time series data with perturbations
Complex systems are characterized by intricate interactions between enti...
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05/30/2023
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction
Diffusion-based manifold learning methods have proven useful in represen...
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03/09/2023
Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection
Training object detection models usually requires instance-level annotat...
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03/03/2023
Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections
Neural ordinary differential equations (Neural ODEs) are an effective fr...
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11/14/2022
Learning predictive checklists from continuous medical data
Checklists, while being only recently introduced in the medical domain, ...
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10/11/2022
Deep Counterfactual Estimation with Categorical Background Variables
Referred to as the third rung of the causal inference ladder, counterfac...
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02/24/2022
Predicting the impact of treatments over time with uncertainty aware neural differential equations
Predicting the impact of treatments from observational data only still r...
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11/25/2021
Learning dynamical systems from data: A simple cross-validation perspective, part III: Irregularly-Sampled Time Series
A simple and interpretable way to learn a dynamical system from data is ...
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10/28/2021
The magnitude vector of images
The magnitude of a finite metric space is a recently-introduced invarian...
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02/15/2021
Topological Graph Neural Networks
Graph neural networks (GNNs) are a powerful architecture for tackling gr...
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11/09/2020
Longitudinal modeling of MS patient trajectories improves predictions of disability progression
Research in Multiple Sclerosis (MS) has recently focused on extracting k...
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07/25/2019
Graph Informer Networks for Molecules
In machine learning, chemical molecules are often represented by sparse ...
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05/29/2019
GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series
Modeling real-world multidimensional time series can be particularly cha...
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11/26/2018
