Search Results for author:
Found 21 papers, 10 papers with code
READ: Large-Scale Neural Scene Rendering for Autonomous Driving
In this paper, a large-scale neural rendering method is proposed to synthesize the autonomous driving scene~(READ), which makes it possible to synthesize large-scale driving scenarios on a PC through a variety of sampling schemes.
Ranked #1 on
Novel View Synthesis
on KITTI
Reconfigurable Intelligent Surface (RIS)-aided Vehicular Networks: Their Protocols, Resource Allocation, and Performance
Reconfigurable intelligent surfaces (RISs) assist in paving the way for the evolution of conventional vehicular networks to autonomous driving.
Innovative semantic communication system
In particular, the semantic communication system for image, namely AESC-I, is designed to verify the feasibility of the new paradigm.
Nonlinear Transform Source-Channel Coding for Semantic Communications
In the considered model, the transmitter first learns a nonlinear analysis transform to map the source data into latent space, then transmits the latent representation to the receiver via deep joint source-channel coding.
Learning to Select Exogenous Events for Marked Temporal Point Process
Marked temporal point processes (MTPPs) have emerged as a powerful modelingtool for a wide variety of applications which are characterized using discreteevents localized in continuous time.
Temporal Clustering with External Memory Network for Disease Progression Modeling
Disease progression modeling (DPM) involves using mathematical frameworks to quantitatively measure the severity of how certain disease progresses.
Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning
In particular, MuViTaNet complements patient representation by using a multi-view encoder to effectively extract information by considering clinical data as both sequences of clinical visits and sets of clinical features.
Contrastive Attention for Automatic Chest X-ray Report Generation
In addition, according to the analysis, the CA model can help existing models better attend to the abnormal regions and provide more accurate descriptions which are crucial for an interpretable diagnosis.
Unveiling personnel movement in a larger indoor area with a non-overlapping multi-camera system
Surveillance cameras are widely applied for indoor occupancy measurement and human movement perception, which benefit for building energy management and social security.
TransICD: Transformer Based Code-wise Attention Model for Explainable ICD Coding
International Classification of Disease (ICD) coding procedure which refers to tagging medical notes with diagnosis codes has been shown to be effective and crucial to the billing system in medical sector.
Giant Inverse Rashba-Edelstein Effect: Application to Monolayer OsBi$_2$
We propose that the hybridization between two sets of Rashba bands can lead to an unconventional topology where the two Fermi circles from different bands own in-plane helical spin textures with the same chiralities, and possess group velocities with the same directions.
Materials Science Mesoscale and Nanoscale Physics
Evaluation of the performance of a ${}^{40}\textrm{Ca}^+ - {}^{27}\textrm{Al}^+$ optical clock
We report the evaluation of the systematic shifts and the total uncertainty of an ${}^{27}\textrm{Al}^+$ optical clock sympathetically cooled by a ${}^{40}\textrm{Ca}^+$ ion.
Atomic Physics
Describing the Migdal effect with a bremsstrahlung-like process and many-body effects
In this paper we incorporate the treatment of the bremsstrahlung process and the electronic many-body effects to give a full description of the Migdal effect in bulk semiconductor targets diamond and silicon.
High Energy Physics - Phenomenology Materials Science
Interpretable Deep Learning for Automatic Diagnosis of 12-lead Electrocardiogram
Deep learning methods have demonstrated promising results in predictive healthcare tasks.
Brain Atlas Guided Attention U-Net for White Matter Hyperintensity Segmentation
In this paper, we propose a novel brain atlas guided attention U-Net (BAGAU-Net) that leverages only FLAIR images with a spatially-registered white matter (WM) brain atlas to yield competitive WMH segmentation performance.
Estimating Individual Treatment Effects with Time-Varying Confounders
Estimating the individual treatment effect (ITE) from observational data is meaningful and practical in healthcare.
When deep learning meets causal inference: a computational framework for drug repurposing from real-world data
Drug repurposing is an effective strategy to identify new uses for existing drugs, providing the quickest possible transition from bench to bedside.
Document Classification for COVID-19 Literature
The global pandemic has made it more important than ever to quickly and accurately retrieve relevant scientific literature for effective consumption by researchers in a wide range of fields.
Codebook-Based Beam Tracking for Conformal ArrayEnabled UAV MmWave Networks
Aiming to address the beam tracking difficulties, we propose to integrate the conformal array (CA) with the surface of each UAV, which enables the full spatial coverage and the agile beam tracking in highly dynamic UAV mmWave networks.
Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations
Our experimental results demonstrate that the recent graph embedding methods achieve promising results and deserve more attention in the future biomedical graph analysis.
Enhancing Interpretability of Black-box Soft-margin SVM by Integrating Data-based Priors
The lack of interpretability often makes black-box models difficult to be applied to many practical domains.
