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05/27/2023
Graph Inductive Biases in Transformers without Message Passing
Transformers for graph data are increasingly widely studied and successf...
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05/02/2023
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems
Recommender systems now consume large-scale data and play a significant ...
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03/08/2023
Diffusing Gaussian Mixtures for Generating Categorical Data
Learning a categorical distribution comes with its own set of challenges...
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02/06/2023
Spectral Augmentations for Graph Contrastive Learning
Contrastive learning has emerged as a premier method for learning repres...
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01/07/2023
Bidirectional Learning for Offline Model-based Biological Sequence Design
Offline model-based optimization aims to maximize a black-box objective ...
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12/29/2022
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network
The mobile communication enabled by cellular networks is the one of the ...
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11/11/2022
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation
To offer accurate and diverse recommendation services, recent methods us...
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10/30/2022
DyG2Vec: Representation Learning for Dynamic Graphs with Self-Supervision
The challenge in learning from dynamic graphs for predictive tasks lies ...
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10/28/2022
Evaluation of Categorical Generative Models – Bridging the Gap Between Real and Synthetic Data
The machine learning community has mainly relied on real data to benchma...
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09/21/2022
Contrastive Learning for Time Series on Dynamic Graphs
There have been several recent efforts towards developing representation...
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09/15/2022
Bidirectional Learning for Offline Infinite-width Model-based Optimization
In offline model-based optimization, we strive to maximize a black-box o...
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08/04/2022
Node Copying: A Random Graph Model for Effective Graph Sampling
There has been an increased interest in applying machine learning techni...
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08/02/2022
Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation
Implicit feedback is frequently used for developing personalized recomme...
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02/22/2022
Bag Graph: Multiple Instance Learning using Bayesian Graph Neural Networks
Multiple Instance Learning (MIL) is a weakly supervised learning problem...
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01/31/2022
Spectral image clustering on dual-energy CT scans using functional regression mixtures
Dual-energy computed tomography (DECT) is an advanced CT scanning techni...
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11/10/2021
Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction
Presently with technology node scaling, an accurate prediction model at ...
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06/10/2021
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting
Spatio-temporal forecasting has numerous applications in analyzing wirel...
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04/17/2021
TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion
Reasoning in a temporal knowledge graph (TKG) is a critical task for inf...
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01/13/2021
Knowledge-Enhanced Top-K Recommendation in Poincaré Ball
Personalized recommender systems are increasingly important as more cont...
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01/13/2021
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation
Personalized recommender systems are playing an increasingly important r...
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11/27/2020
GraphSeam: Supervised Graph Learning Framework for Semantic UV Mapping
Recently there has been a significant effort to automate UV mapping, the...
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08/25/2020
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems
Given the convenience of collecting information through online services,...
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07/09/2020
Node Copying for Protection Against Graph Neural Network Topology Attacks
Adversarial attacks can affect the performance of existing deep learning...
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07/09/2020
Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation
Node classification in attributed graphs is an important task in multipl...
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06/23/2020
Non-Parametric Graph Learning for Bayesian Graph Neural Networks
Graphs are ubiquitous in modelling relational structures. Recent endeavo...
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01/01/2020
Multi-Graph Convolution Collaborative Filtering
Personalized recommendation is ubiquitous, playing an important role in ...
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12/26/2019
Memory Augmented Graph Neural Networks for Sequential Recommendation
The chronological order of user-item interactions can reveal time-evolvi...
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11/08/2019
Bayesian Graph Convolutional Neural Networks using Node Copying
Graph convolutional neural networks (GCNN) have numerous applications in...
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10/26/2019
Bayesian Graph Convolutional Neural Networks Using Non-Parametric Graph Learning
Graph convolutional neural networks (GCNN) have been successfully applie...
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06/06/2019
Learning Gaussian Graphical Models with Ordered Weighted L1 Regularization
We address the task of identifying densely connected subsets of multivar...
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11/27/2018
Bayesian graph convolutional neural networks for semi-supervised classification
Recently, techniques for applying convolutional neural networks to graph...
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07/06/2018
Invertible Particle Flow-based Sequential MCMC with extension to Gaussian Mixture noise models
Sequential state estimation in non-linear and non-Gaussian state spaces ...
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09/21/2017
Cost Adaptation for Robust Decentralized Swarm Behaviour
The multi-agent swarm system is a robust paradigm which can drive effici...
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02/24/2017
Microwave breast cancer detection using Empirical Mode Decomposition features
Microwave-based breast cancer detection has been proposed as a complemen...
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02/19/2016
Semi-parametric Order-based Generalized Multivariate Regression
In this paper, we consider a generalized multivariate regression problem...
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02/25/2015
Sparse Multivariate Factor Regression
We consider the problem of multivariate regression in a setting where th...
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05/05/2011
GANC: Greedy Agglomerative Normalized Cut
This paper describes a graph clustering algorithm that aims to minimize ...
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09/09/2009
