Search Results for author:
Found 21 papers, 2 papers with code
MonoBox: Tightness-free Box-supervised Polyp Segmentation using Monotonicity Constraint
We propose MonoBox, an innovative box-supervised segmentation method constrained by monotonicity to liberate its training from the user-unfriendly box-tightness assumption.
Node Centrality Approximation For Large Networks Based On Inductive Graph Neural Networks
Closeness Centrality (CC) and Betweenness Centrality (BC) are crucial metrics in network analysis, providing essential reference for discerning the significance of nodes within complex networks.
A Quick Framework for Evaluating Worst Robustness of Complex Networks
Robustness is pivotal for comprehending, designing, optimizing, and rehabilitating networks, with simulation attacks being the prevailing evaluation method.
Deep MSFOP: Multiple Spectral filter Operators Preservation in Deep Functional Maps for Unsupervised Shape Matching
We propose a novel constraint called Multiple Spectral filter Operators Preservation (MSFOR) to compute functional maps and based on it, develop an efficient deep functional map architecture called Deep MSFOP for shape matching.
Conditional Stochastic Interpolation for Generative Learning
We propose a conditional stochastic interpolation (CSI) approach to learning conditional distributions.
Optimal Clustering of Discrete Mixtures: Binomial, Poisson, Block Models, and Multi-layer Networks
Under the mixture multi-layer stochastic block model (MMSBM), we show that the minimax optimal network clustering error rate, which takes an exponential form and is characterized by the Renyi divergence between the edge probability distributions of the component networks.
IBoxCLA: Towards Robust Box-supervised Segmentation of Polyp via Improved Box-dice and Contrastive Latent-anchors
In response, we propose two innovative learning fashions, Improved Box-dice (IBox) and Contrastive Latent-Anchors (CLA), and combine them to train a robust box-supervised model IBoxCLA.
CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model
It is specifically designed for code-related tasks with both English and Chinese prompts and supports over 40 programming languages.
Spatio-Temporal Contrastive Self-Supervised Learning for POI-level Crowd Flow Inference
To address these challenges, we recast the crowd flow inference problem as a self-supervised attributed graph representation learning task and introduce a novel Contrastive Self-learning framework for Spatio-Temporal data (CSST).
GPU Accelerated Color Correction and Frame Warping for Real-time Video Stitching
Traditional image stitching focuses on a single panorama frame without considering the spatial-temporal consistency in videos.
Evaluating Dynamic Conditional Quantile Treatment Effects with Applications in Ridesharing
However, assessing dynamic quantile treatment effects (QTE) remains a challenge, particularly when dealing with data from ride-sourcing platforms that involve sequential decision-making across time and space.
DUFormer: Solving Power Line Detection Task in Aerial Images using Semantic Segmentation
Unmanned aerial vehicles (UAVs) are frequently used for inspecting power lines and capturing high-resolution aerial images.
rMultiNet: An R Package For Multilayer Networks Analysis
This paper develops an R package rMultiNet to analyze multilayer network data.
Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting
In this paper, we propose Regularized Graph Structure Learning (RGSL) model to incorporate both explicit prior structure and implicit structure together, and learn the forecasting deep networks along with the graph structure.
A Deep Learning Approach to Predicting Ventilator Parameters for Mechanically Ventilated Septic Patients
We develop a deep learning approach to predicting a set of ventilator parameters for a mechanically ventilated septic patient using a long and short term memory (LSTM) recurrent neural network (RNN) model.
Robust Protection of III-V Nanowires in Water Splitting by a Thin Compact TiO$_2$ Layer
Working as a photocathode for water splitting, they exhibited a 45% larger photocurrent density compared with un-protected counterparts and a high Faraday efficiency of 91%, and can also maintain a record-long highly-stable performance among narrow-bandgap III-V NW photoelectrodes; after 67 hours photoelectrochemical stability test reaction in strong acid electrolyte solution (pH = 1), they show no apparent indication of corrosion, which is in stark contrast to the un-protected NWs that are fully failed after 35-hours.
Mesoscale and Nanoscale Physics Chemical Physics
Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances and Weak Lensing
We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset.
Cosmology and Nongalactic Astrophysics
Community Detection on Mixture Multi-layer Networks via Regularized Tensor Decomposition
We show that the TWIST procedure can accurately detect the communities with small misclassification error as the number of nodes and/or the number of layers increases.
Semi-supervised learning in unbalanced and heterogeneous networks
Community detection was a hot topic on network analysis, where the main aim is to perform unsupervised learning or clustering in networks.
Classification of normal/abnormal heart sound recordings based on multi-domain features and back propagation neural network
The proposed framework for this challenge has four steps: preprocessing, feature extraction, training and validation.
