Search Results for author:
Found 52 papers, 36 papers with code
Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM
Summary: BWA-MEM is a new alignment algorithm for aligning sequence reads or long query sequences against a large reference genome such as human.
Ranked #3 on
3D Object Reconstruction From A Single Image
on RenderPeople
(using extra training data)
Towards Better Understanding of Artifacts in Variant Calling from High-Coverage Samples
By investigating false heterozygous calls in the haploid genome, we identified the erroneous realignment in low-complexity regions and the incomplete reference genome with respect to the sample as the two major sources of errors, which press for continued improvements in these two areas.
Minimap2: pairwise alignment for nucleotide sequences
Motivation: Recent advances in sequencing technologies promise ultra-long reads of $\sim$100 kilo bases (kb) in average, full-length mRNA or cDNA reads in high throughput and genomic contigs over 100 mega bases (Mb) in length.
Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning
The first one is lack of collaboration between scenarios meaning that each strategy maximizes its own objective but ignores the goals of other strategies, leading to a sub-optimal overall performance.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
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.
Identifying centromeric satellites with dna-brnn
Summary: Human alpha satellite and satellite 2/3 contribute to several percent of the human genome.
Deep Learning of Subsurface Flow via Theory-guided Neural Network
The TgNN can achieve higher accuracy than the ordinary Artificial Neural Network (ANN) because the former provides physically feasible predictions and can be more readily generalized beyond the regimes covered with the training data.
Logram: Efficient Log Parsing Using n-Gram Dictionaries
As logs are usually very large in size, automated log analysis is needed to assist practitioners in their software operation and maintenance efforts.
Software Engineering
The design and construction of reference pangenome graphs
The recent advances in sequencing technologies enables the assembly of individual genomes to the reference quality.
Haplotype-resolved de novo assembly with phased assembly graphs
Haplotype-resolved de novo assembly is the ultimate solution to the study of sequence variations in a genome.
Genomics Quantitative Methods
BGM: Building a Dynamic Guidance Map without Visual Images for Trajectory Prediction
Visual images usually contain the informative context of the environment, thereby helping to predict agents' behaviors.
Twelve years of SAMtools and BCFtools
Background SAMtools and BCFtools are widely used programs for processing and analysing high-throughput sequencing data.
End-to-End Rotation Averaging With Multi-Source Propagation
These methods can suffer from bad initializations due to the noisy spanning tree or outliers in input relative rotations.
New strategies to improve minimap2 alignment accuracy
Summary: We present several recent improvements to minimap2, a versatile pairwise aligner for nucleotide sequences.
Robust haplotype-resolved assembly of diploid individuals without parental data
Routine single-sample haplotype-resolved assembly remains an unresolved problem.
Constructing Sub-scale Surrogate Model for Proppant Settling in Inclined Fractures from Simulation Data with Multi-fidelity Neural Network
The results demonstrate that constructing the settling surrogate with the MFNN can reduce the need for high-fidelity data and thus computational cost by 80%, while the accuracy lost is less than 5% compared to a high-fidelity surrogate.
Integrating Attention Feedback into the Recurrent Neural Network
The HA-LSTM structure is different from the standard LSTM structure because a scaled dot-product attention-based sliding controller is introduced to the LSTM structure.
Metagenome assembly of high-fidelity long reads with hifiasm-meta
Current metagenome assemblers developed for short sequence reads or noisy long readswere not optimized for accurate long reads.
A comparative study of non-deep learning, deep learning, and ensemble learning methods for sunspot number prediction
An open-source Python package of our XGBoost-DL for the sunspot number prediction is available at https://github. com/yd1008/ts_ensemble_sunspot.
FB-MSTCN: A Full-Band Single-Channel Speech Enhancement Method Based on Multi-Scale Temporal Convolutional Network
In recent years, deep learning-based approaches have significantly improved the performance of single-channel speech enhancement.
An Annotation-free Restoration Network for Cataractous Fundus Images
The restoration model is learned from the synthesized images and adapted to real cataract images.
Studying the Practices of Deploying Machine Learning Projects on Docker
Studies have recently explored the use of Docker for deploying general software projects with no specific focus on how Docker is used to deploy ML-based projects.
Structure-consistent Restoration Network for Cataract Fundus Image Enhancement
In this paper, to circumvent the strict deployment requirement, a structure-consistent restoration network (SCR-Net) for cataract fundus images is developed from synthesized data that shares an identical structure.
Fast sequence to graph alignment using the graph wavefront algorithm
Motivation: A pan-genome graph represents a collection of genomes and encodes sequence variations between them.
An Empirical Study on the Usage of Automated Machine Learning Tools
Machine learning (ML) practitioners use AutoML tools to automate and optimize the process of feature engineering, model training, and hyperparameter optimization and so on.
Spacecraft Attitude Pointing Control under Pointing Forbidden Constraints with Guaranteed Accuracy
To resolve this problem, a switching controller structure is proposed in this paper based on the reduced-attitude representation, fusing the artificial potential field (APF) methodology and the Prescribed Performance Control (PPC) scheme together.
Towards complete representation of bacterial contents in metagenomic samples
Our algorithm generates more circular MAGs and moves a step closer to the complete representation of microbiome communities.
Protein-to-genome alignment with miniprot
Motivation: Protein-to-genome alignment is critical to annotating genes in non-model organisms.
Degradation-invariant Enhancement of Fundus Images via Pyramid Constraint Network
For boosting the clinical deployment of fundus image enhancement, this paper proposes the pyramid constraint to develop a degradation-invariant enhancement network (PCE-Net), which mitigates the demand for clinical data and stably enhances unknown data.
RAGO: Recurrent Graph Optimizer For Multiple Rotation Averaging
Our graph optimizer iteratively refines the global camera rotations by minimizing each node's single rotation objective function.
Foreground and Text-lines Aware Document Image Rectification
In this paper, we focus on the foreground and text-line regions of distorted paper and proposes a global and local fusion method to improve the rectification effect of distorted images and enhance the readability of document images.
Dense RGB SLAM with Neural Implicit Maps
To reach this challenging goal without depth input, we introduce a hierarchical feature volume to facilitate the implicit map decoder.
3D Former: Monocular Scene Reconstruction with 3D SDF Transformers
In this work, we propose an SDF transformer network, which replaces the role of 3D CNN for better 3D feature aggregation.
De novo reconstruction of satellite repeat units from sequence data
Existing algorithms for identifying satellite repeats either require the complete assembly of satellites or only work for simple repeat structures without HORs.
What Causes Exceptions in Machine Learning Applications? Mining Machine Learning-Related Stack Traces on Stack Overflow
Thus, studying the patterns in stack traces can help practitioners and researchers understand the causes of exceptions in ML applications and the challenges faced by ML developers.
Learnable Ophthalmology SAM
Based on Segment Anything (SAM), we propose a simple but effective learnable prompt layer suitable for multiple target segmentation in ophthalmology multi-modal images, named Learnable Ophthalmology Segment Anything (SAM).
Scalable telomere-to-telomere assembly for diploid and polyploid genomes with double graph
Despite recent advances in the length and the accuracy of long-read data, building haplotype-resolved genome assemblies from telomere to telomere still requires considerable computational resources.
Efficient Backdoor Attacks for Deep Neural Networks in Real-world Scenarios
However, existing backdoor attack methods make unrealistic assumptions, assuming that all training data comes from a single source and that attackers have full access to the training data.
Frequency-mixed Single-source Domain Generalization for Medical Image Segmentation
Consequently, domain generalization (DG) is developed to boost the performance of segmentation models on unseen domains.
Optimal battery thermal management for electric vehicles with battery degradation minimization
A control-oriented onboard BTMS model is proposed and verified under different speed profiles and temperatures.
Genome assembly in the telomere-to-telomere era
De novo assembly is the process of reconstructing the genome sequence of an organism from sequencing reads.
On the Effectiveness of Log Representation for Log-based Anomaly Detection
We believe our comprehensive comparison of log representation techniques can help researchers and practitioners better understand the characteristics of different log representation techniques and provide them with guidance for selecting the most suitable ones for their ML-based log analysis workflow.
Deploying Deep Reinforcement Learning Systems: A Taxonomy of Challenges
In this paper, we propose an empirical study on Stack Overflow (SO), the most popular Q&A forum for developers, to uncover and understand the challenges practitioners faced when deploying DRL systems.
A Generic Fundus Image Enhancement Network Boosted by Frequency Self-supervised Representation Learning
Fundus photography is prone to suffer from image quality degradation that impacts clinical examination performed by ophthalmologists or intelligent systems.
ACT-Net: Anchor-context Action Detection in Surgery Videos
In this paper, to accurately detect fine-grained actions that happen at every moment, we propose an anchor-context action detection network (ACTNet), including an anchor-context detection (ACD) module and a class conditional diffusion (CCD) module, to answer the following questions: 1) where the actions happen; 2) what actions are; 3) how confidence predictions are.
AutoRepo: A general framework for multi-modal LLM-based automated construction reporting
Ensuring the safety, quality, and timely completion of construction projects is paramount, with construction inspections serving as a vital instrument towards these goals.
Enhancing and Adapting in the Clinic: Source-free Unsupervised Domain Adaptation for Medical Image Enhancement
Additionally, a pseudo-label picker is developed to boost the knowledge distillation of enhancement tasks.
TDeLTA: A Light-weight and Robust Table Detection Method based on Learning Text Arrangement
The diversity of tables makes table detection a great challenge, leading to existing models becoming more tedious and complex.
Characterizing and Classifying Developer Forum Posts with their Intentions
The modeling of the intentions of posts can provide an extra dimension to the current tag taxonomy.
Refining GPT-3 Embeddings with a Siamese Structure for Technical Post Duplicate Detection
When applied to the dataset we constructed with a recent Stack Overflow dump, our approach attains a Top-1, Top-5, and Top-30 accuracy of 23. 1%, 43. 9%, and 68. 9%, respectively.
Exploring gene content with pangenome gene graphs
Although tools have been developed to identify gene content changes in bacterial genomes, none is applicable to collections of large eukaryotic genomes such as the human pangenome.
