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Found 13 papers, 5 papers with code
LocalGCL: Local-aware Contrastive Learning for Graphs
Graph representation learning (GRL) makes considerable progress recently, which encodes graphs with topological structures into low-dimensional embeddings.
Retrieval-Augmented Generation for Large Language Models: A Survey
Large Language Models (LLMs) showcase impressive capabilities but encounter challenges like hallucination, outdated knowledge, and non-transparent, untraceable reasoning processes.
AI-driven projection tomography with multicore fibre-optic cell rotation
The performance of the proposed cell rotation tomography approach is validated through the three-dimensional reconstruction of cell phantoms and HL60 human cancer cells.
Calibration-free quantitative phase imaging in multi-core fiber endoscopes using end-to-end deep learning
Quantitative phase imaging (QPI) through multi-core fibers (MCFs) has been an emerging in vivo label-free endoscopic imaging modality with minimal invasiveness.
Flames: Benchmarking Value Alignment of LLMs in Chinese
The widespread adoption of large language models (LLMs) across various regions underscores the urgent need to evaluate their alignment with human values.
DriveSceneGen: Generating Diverse and Realistic Driving Scenarios from Scratch
Realistic and diverse traffic scenarios in large quantities are crucial for the development and validation of autonomous driving systems.
Toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptation
Machine learning head models (MLHMs) are developed to estimate brain deformation for early detection of traumatic brain injury (TBI).
On Understanding and Mitigating the Dimensional Collapse of Graph Contrastive Learning: a Non-Maximum Removal Approach
Graph Contrastive Learning (GCL) has shown promising performance in graph representation learning (GRL) without the supervision of manual annotations.
Lensless multicore-fiber microendoscope for real-time tailored light field generation with phase encoder neural network (CoreNet)
The generation of tailored light with multi-core fiber (MCF) lensless microendoscopes is widely used in biomedicine.
RISA-Net: Rotation-Invariant Structure-Aware Network for Fine-Grained 3D Shape Retrieval
Fine-grained 3D shape retrieval aims to retrieve 3D shapes similar to a query shape in a repository with models belonging to the same class, which requires shape descriptors to be capable of representing detailed geometric information to discriminate shapes with globally similar structures.
Effective and Efficient Batch Normalization Using Few Uncorrelated Data for Statistics' Estimation
We identify that the effectiveness expects less data correlation while the efficiency expects regular execution pattern.
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i. e., 2012-2018.
Batch Normalization Sampling
In this paper, we propose alleviating this problem through sampling only a small fraction of data for normalization at each iteration.
