Search Results for author:
Found 12 papers, 5 papers with code
TempGNN: Temporal Graph Neural Networks for Dynamic Session-Based Recommendations
Session-based recommendations which predict the next action by understanding a user's interaction behavior with items within a relatively short ongoing session have recently gained increasing popularity.
DeepOnto: A Python Package for Ontology Engineering with Deep Learning
Integrating deep learning techniques, particularly language models (LMs), with knowledge representation techniques like ontologies has raised widespread attention, urging the need of a platform that supports both paradigms.
Accurate Bundle Matching and Generation via Multitask Learning with Partially Shared Parameters
BundleMage effectively mixes user preferences of items and bundles using an adaptive gate technique to achieve high accuracy for the bundle matching.
SR-GCL: Session-Based Recommendation with Global Context Enhanced Augmentation in Contrastive Learning
As a crucial component of contrastive learning, we propose two global context enhanced data augmentation methods while maintaining the semantics of the original session.
STING: Self-attention based Time-series Imputation Networks using GAN
Although recent works based on deep neural networks have shown remarkable results, they still have a limitation to capture the complex generation process of the multivariate time series.
Revisiting Image Pyramid Structure for High Resolution Salient Object Detection
Salient object detection (SOD) has been in the spotlight recently, yet has been studied less for high-resolution (HR) images.
Ranked #1 on
RGB Salient Object Detection
on ECSSD
A Style-aware Discriminator for Controllable Image Translation
Current image-to-image translations do not control the output domain beyond the classes used during training, nor do they interpolate between different domains well, leading to implausible results.
Image Manipulation
Multimodal Unsupervised Image-To-Image Translation
+1
Finding essential parts of the brain in rs-fMRI can improve diagnosing ADHD by Deep Learning
As a result, when we only used 15 important region of interest(ROIs) for training, an accuracy of 70. 6% was obtained, significantly exceeding the existing results of 68. 6% from all ROIs.
UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation
We construct a modified version of U-Net shape network with additional encoder and decoder and compute a saliency map in each bottom-up stream prediction module and propagate to the next prediction module.
Ranked #8 on
Medical Image Segmentation
on ETIS-LARIBPOLYPDB
SpaceMeshLab: Spatial Context Memoization and Meshgrid Atrous Convolution Consensus for Semantic Segmentation
For this reason, we propose Spatial Context Memoization (SpaM), a bypassing branch for spatial context by retaining the input dimension and constantly communicating its spatial context and rich semantic information mutually with the backbone network.
Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendations
Personalized recommendations are the backbone machine learning (ML) algorithm that powers several important application domains (e. g., ads, e-commerce, etc) serviced from cloud datacenters.
Fast and Accurate Transferability Measurement for Heterogeneous Multivariate Data
We address the problem of measuring transferability between source and target datasets, where the source and the target have different feature spaces and distributions.
