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06/28/2022
Graph Condensation via Receptive Field Distribution Matching
Graph neural networks (GNNs) enable the analysis of graphs using deep le...
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05/23/2022
uGLAD: Sparse graph recovery by optimizing deep unrolled networks
Probabilistic Graphical Models (PGMs) are generative models of complex s...
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12/14/2021
Efficient Dynamic Graph Representation Learning at Scale
Dynamic graphs with ordered sequences of events between nodes are preval...
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11/03/2021
Multi-task Learning of Order-Consistent Causal Graphs
We consider the problem of discovering K related Gaussian directed acycl...
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06/24/2020
Understanding Deep Architectures with Reasoning Layer
Recently, there has been a surge of interest in combining deep learning ...
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06/09/2020
Learning to Stop While Learning to Predict
There is a recent surge of interest in designing deep architectures base...
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02/13/2020
RNA Secondary Structure Prediction By Learning Unrolled Algorithms
In this paper, we propose an end-to-end deep learning model, called E2Ef...
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01/29/2020
Efficient Probabilistic Logic Reasoning with Graph Neural Networks
Markov Logic Networks (MLNs), which elegantly combine logic rules and pr...
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11/01/2019
Review: Ordinary Differential Equations For Deep Learning
To better understand and improve the behavior of neural networks, a rece...
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06/05/2019
Can Graph Neural Networks Help Logic Reasoning?
Effectively combining logic reasoning and probabilistic inference has be...
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06/01/2019
GLAD: Learning Sparse Graph Recovery
Recovering sparse conditional independence graphs from data is a fundame...
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02/02/2019
Meta Particle Flow for Sequential Bayesian Inference
We present a particle flow realization of Bayes' rule, where an ODE-base...
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02/02/2019
Parametric FEM for Shape Optimization applied to Golgi Stack
The thesis is about an application of the shape optimization to the morp...
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12/27/2018
Generative Adversarial User Model for Reinforcement Learning Based Recommendation System
There are great interests as well as many challenges in applying reinfor...
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12/27/2018