Search Results for author: Heng Li

Found 32 papers, 21 papers with code

3D Former: Monocular Scene Reconstruction with 3D SDF Transformers

no code implementations31 Jan 2023 Weihao Yuan, Xiaodong Gu, Heng Li, Zilong Dong, Siyu Zhu

In this work, we propose an SDF transformer network, which replaces the role of 3D CNN for better 3D feature aggregation.

Dense RGB SLAM with Neural Implicit Maps

no code implementations21 Jan 2023 Heng Li, Xiaodong Gu, Weihao Yuan, Luwei Yang, Zilong Dong, Ping Tan

To reach this challenging goal without depth input, we introduce a hierarchical feature volume to facilitate the implicit map decoder.

Simultaneous Localization and Mapping

RAGO: Recurrent Graph Optimizer For Multiple Rotation Averaging

1 code implementation CVPR 2022 Heng Li, Zhaopeng Cui, Shuaicheng Liu, Ping Tan

Our graph optimizer iteratively refines the global camera rotations by minimizing each node's single rotation objective function.

Degradation-invariant Enhancement of Fundus Images via Pyramid Constraint Network

1 code implementation18 Oct 2022 Haofeng Liu, Heng Li, Huazhu Fu, Ruoxiu Xiao, Yunshu Gao, Yan Hu, Jiang Liu

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.

Image Enhancement

Protein-to-genome alignment with miniprot

1 code implementation14 Oct 2022 Heng Li

Motivation: Protein-to-genome alignment is critical to annotating genes in non-model organisms.

Towards complete representation of bacterial contents in metagenomic samples

no code implementations30 Sep 2022 Xiaowen Feng, Heng Li

Our algorithm generates more circular MAGs and moves a step closer to the complete representation of microbiome communities.

Spacecraft Attitude Pointing Control under Pointing Forbidden Constraints with Guaranteed Accuracy

no code implementations13 Sep 2022 Jiakun Lei, Tao Meng, Weijia Wang, Shujian Sun, Heng Li, Zhonghe Jin

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.

An Empirical Study on the Usage of Automated Machine Learning Tools

1 code implementation28 Aug 2022 Forough Majidi, Moses Openja, Foutse khomh, Heng Li

Machine learning (ML) practitioners use AutoML tools to automate and optimize the process of feature engineering, model training, and hyperparameter optimization and so on.

Feature Engineering Hyperparameter Optimization +1

Fast sequence to graph alignment using the graph wavefront algorithm

1 code implementation27 Jun 2022 Haowen Zhang, Shiqi Wu, Srinivas Aluru, Heng Li

Motivation: A pan-genome graph represents a collection of genomes and encodes sequence variations between them.

Structure-consistent Restoration Network for Cataract Fundus Image Enhancement

1 code implementation9 Jun 2022 Heng Li, Haofeng Liu, Huazhu Fu, Hai Shu, Yitian Zhao, Xiaoling Luo, Yan Hu, Jiang Liu

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.

Image Enhancement

Studying the Practices of Deploying Machine Learning Projects on Docker

no code implementations1 Jun 2022 Moses Openja, Forough Majidi, Foutse khomh, Bhagya Chembakottu, Heng Li

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.

BIG-bench Machine Learning Management

An Annotation-free Restoration Network for Cataractous Fundus Images

1 code implementation15 Mar 2022 Heng Li, Haofeng Liu, Yan Hu, Huazhu Fu, Yitian Zhao, Hanpei Miao, Jiang Liu

The restoration model is learned from the synthesized images and adapted to real cataract images.

A comparative study of non-deep learning, deep learning, and ensemble learning methods for sunspot number prediction

1 code implementation11 Mar 2022 Yuchen Dang, Ziqi Chen, Heng Li, Hai Shu

An open-source Python package of our XGBoost-DL for the sunspot number prediction is available at https://github. com/yd1008/ts_ensemble_sunspot.

Ensemble Learning

Metagenome assembly of high-fidelity long reads with hifiasm-meta

1 code implementation16 Oct 2021 Xiaowen Feng, Haoyu Cheng, Daniel Portik, Heng Li

Current metagenome assemblers developed for short sequence reads or noisy long readswere not optimized for accurate long reads.

Integrating Attention Feedback into the Recurrent Neural Network

1 code implementation29 Sep 2021 Heng Li

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.

text-classification Text Classification +1

Constructing Sub-scale Surrogate Model for Proppant Settling in Inclined Fractures from Simulation Data with Multi-fidelity Neural Network

no code implementations25 Sep 2021 Pengfei Tang, Junsheng Zeng, Dongxiao Zhang, Heng Li

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.

New strategies to improve minimap2 alignment accuracy

1 code implementation7 Aug 2021 Heng Li

Summary: We present several recent improvements to minimap2, a versatile pairwise aligner for nucleotide sequences.

End-to-End Rotation Averaging With Multi-Source Propagation

1 code implementation CVPR 2021 Luwei Yang, Heng Li, Jamal Ahmed Rahim, Zhaopeng Cui, Ping Tan

These methods can suffer from bad initializations due to the noisy spanning tree or outliers in input relative rotations.

Twelve years of SAMtools and BCFtools

2 code implementations18 Dec 2020 Petr Danecek, James K. Bonfield, Jennifer Liddle, John Marshall, Valeriu Ohan, Martin O Pollard, Andrew Whitwham, Thomas Keane, Shane A. McCarthy, Robert M. Davies, Heng Li

Background SAMtools and BCFtools are widely used programs for processing and analysing high-throughput sequencing data.

BGM: Building a Dynamic Guidance Map without Visual Images for Trajectory Prediction

no code implementations8 Oct 2020 Beihao Xia, Conghao Wong, Heng Li, Shiming Chen, Qinmu Peng, Xinge You

Visual images usually contain the informative context of the environment, thereby helping to predict agents' behaviors.

Trajectory Prediction

Haplotype-resolved de novo assembly with phased assembly graphs

no code implementations3 Aug 2020 Haoyu Cheng, Gregory T Concepcion, Xiaowen Feng, Haowen Zhang, Heng Li

Haplotype-resolved de novo assembly is the ultimate solution to the study of sequence variations in a genome.

Genomics Quantitative Methods

The design and construction of reference pangenome graphs

1 code implementation13 Mar 2020 Heng Li, Xiaowen Feng, Chong Chu

The recent advances in sequencing technologies enables the assembly of individual genomes to the reference quality.

Logram: Efficient Log Parsing Using n-Gram Dictionaries

1 code implementation7 Jan 2020 Hetong Dai, Heng Li, Weiyi Shang, Tse-Hsun Chen, Che-Shao Chen

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

Deep Learning of Subsurface Flow via Theory-guided Neural Network

no code implementations24 Oct 2019 Nanzhe Wang, Dongxiao Zhang, Haibin Chang, Heng Li

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.

Transfer Learning

Identifying centromeric satellites with dna-brnn

1 code implementation22 Jan 2019 Heng Li

Summary: Human alpha satellite and satellite 2/3 contribute to several percent of the human genome.

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

1 code implementation5 Nov 2018 Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipkova, John Freymann, Justin Kirby, Michel Bilello, Hassan Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka Colen, Aikaterini Kotrotsou, Pamela Lamontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc-Andre Weber, Abhishek Mahajan, Ujjwal Baid, Elizabeth Gerstner, Dongjin Kwon, Gagan Acharya, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Francisco J. Albiol, Varghese Alex, Nigel Allinson, Pedro H. A. Amorim, Abhijit Amrutkar, Ganesh Anand, Simon Andermatt, Tal Arbel, Pablo Arbelaez, Aaron Avery, Muneeza Azmat, Pranjal B., W Bai, Subhashis Banerjee, Bill Barth, Thomas Batchelder, Kayhan Batmanghelich, Enzo Battistella, Andrew Beers, Mikhail Belyaev, Martin Bendszus, Eze Benson, Jose Bernal, Halandur Nagaraja Bharath, George Biros, Sotirios Bisdas, James Brown, Mariano Cabezas, Shilei Cao, Jorge M. Cardoso, Eric N Carver, Adrià Casamitjana, Laura Silvana Castillo, Marcel Catà, Philippe Cattin, Albert Cerigues, Vinicius S. Chagas, Siddhartha Chandra, Yi-Ju Chang, Shiyu Chang, Ken Chang, Joseph Chazalon, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Chen, Kun Cheng, Ahana Roy Choudhury, Roger Chylla, Albert Clérigues, Steven Colleman, Ramiro German Rodriguez Colmeiro, Marc Combalia, Anthony Costa, Xiaomeng Cui, Zhenzhen Dai, Lutao Dai, Laura Alexandra Daza, Eric Deutsch, Changxing Ding, Chao Dong, Shidu Dong, Wojciech Dudzik, Zach Eaton-Rosen, Gary Egan, Guilherme Escudero, Théo Estienne, Richard Everson, Jonathan Fabrizio, Yong Fan, Longwei Fang, Xue Feng, Enzo Ferrante, Lucas Fidon, Martin Fischer, Andrew P. French, Naomi Fridman, Huan Fu, David Fuentes, Yaozong Gao, Evan Gates, David Gering, Amir Gholami, Willi Gierke, Ben Glocker, Mingming Gong, Sandra González-Villá, T. Grosges, Yuanfang Guan, Sheng Guo, Sudeep Gupta, Woo-Sup Han, Il Song Han, Konstantin Harmuth, Huiguang He, Aura Hernández-Sabaté, Evelyn Herrmann, Naveen Himthani, Winston Hsu, Cheyu Hsu, Xiaojun Hu, Xiaobin Hu, Yan Hu, Yifan Hu, Rui Hua, Teng-Yi Huang, Weilin Huang, Sabine Van Huffel, Quan Huo, Vivek HV, Khan M. Iftekharuddin, Fabian Isensee, Mobarakol Islam, Aaron S. Jackson, Sachin R. Jambawalikar, Andrew Jesson, Weijian Jian, Peter Jin, V Jeya Maria Jose, Alain Jungo, B Kainz, Konstantinos Kamnitsas, Po-Yu Kao, Ayush Karnawat, Thomas Kellermeier, Adel Kermi, Kurt Keutzer, Mohamed Tarek Khadir, Mahendra Khened, Philipp Kickingereder, Geena Kim, Nik King, Haley Knapp, Urspeter Knecht, Lisa Kohli, Deren Kong, Xiangmao Kong, Simon Koppers, Avinash Kori, Ganapathy Krishnamurthi, Egor Krivov, Piyush Kumar, Kaisar Kushibar, Dmitrii Lachinov, Tryphon Lambrou, Joon Lee, Chengen Lee, Yuehchou Lee, M Lee, Szidonia Lefkovits, Laszlo Lefkovits, James Levitt, Tengfei Li, Hongwei Li, Hongyang Li, Xiaochuan Li, Yuexiang Li, Heng Li, Zhenye Li, Xiaoyu Li, Zeju Li, Xiaogang Li, Wenqi Li, Zheng-Shen Lin, Fengming Lin, Pietro Lio, Chang Liu, Boqiang Liu, Xiang Liu, Mingyuan Liu, Ju Liu, Luyan Liu, Xavier Llado, Marc Moreno Lopez, Pablo Ribalta Lorenzo, Zhentai Lu, Lin Luo, Zhigang Luo, Jun Ma, Kai Ma, Thomas Mackie, Anant Madabushi, Issam Mahmoudi, Klaus H. Maier-Hein, Pradipta Maji, CP Mammen, Andreas Mang, B. S. Manjunath, Michal Marcinkiewicz, S McDonagh, Stephen McKenna, Richard McKinley, Miriam Mehl, Sachin Mehta, Raghav Mehta, Raphael Meier, Christoph Meinel, Dorit Merhof, Craig Meyer, Robert Miller, Sushmita Mitra, Aliasgar Moiyadi, David Molina-Garcia, Miguel A. B. Monteiro, Grzegorz Mrukwa, Andriy Myronenko, Jakub Nalepa, Thuyen Ngo, Dong Nie, Holly Ning, Chen Niu, Nicholas K Nuechterlein, Eric Oermann, Arlindo Oliveira, Diego D. C. Oliveira, Arnau Oliver, Alexander F. I. Osman, Yu-Nian Ou, Sebastien Ourselin, Nikos Paragios, Moo Sung Park, Brad Paschke, J. Gregory Pauloski, Kamlesh Pawar, Nick Pawlowski, Linmin Pei, Suting Peng, Silvio M. Pereira, Julian Perez-Beteta, Victor M. Perez-Garcia, Simon Pezold, Bao Pham, Ashish Phophalia, Gemma Piella, G. N. Pillai, Marie Piraud, Maxim Pisov, Anmol Popli, Michael P. Pound, Reza Pourreza, Prateek Prasanna, Vesna Prkovska, Tony P. Pridmore, Santi Puch, Élodie Puybareau, Buyue Qian, Xu Qiao, Martin Rajchl, Swapnil Rane, Michael Rebsamen, Hongliang Ren, Xuhua Ren, Karthik Revanuru, Mina Rezaei, Oliver Rippel, Luis Carlos Rivera, Charlotte Robert, Bruce Rosen, Daniel Rueckert, Mohammed Safwan, Mostafa Salem, Joaquim Salvi, Irina Sanchez, Irina Sánchez, Heitor M. Santos, Emmett Sartor, Dawid Schellingerhout, Klaudius Scheufele, Matthew R. Scott, Artur A. Scussel, Sara Sedlar, Juan Pablo Serrano-Rubio, N. Jon Shah, Nameetha Shah, Mazhar Shaikh, B. Uma Shankar, Zeina Shboul, Haipeng Shen, Dinggang Shen, Linlin Shen, Haocheng Shen, Varun Shenoy, Feng Shi, Hyung Eun Shin, Hai Shu, Diana Sima, M Sinclair, Orjan Smedby, James M. Snyder, Mohammadreza Soltaninejad, Guidong Song, Mehul Soni, Jean Stawiaski, Shashank Subramanian, Li Sun, Roger Sun, Jiawei Sun, Kay Sun, Yu Sun, Guoxia Sun, Shuang Sun, Yannick R Suter, Laszlo Szilagyi, Sanjay Talbar, DaCheng Tao, Zhongzhao Teng, Siddhesh Thakur, Meenakshi H Thakur, Sameer Tharakan, Pallavi Tiwari, Guillaume Tochon, Tuan Tran, Yuhsiang M. Tsai, Kuan-Lun Tseng, Tran Anh Tuan, Vadim Turlapov, Nicholas Tustison, Maria Vakalopoulou, Sergi Valverde, Rami Vanguri, Evgeny Vasiliev, Jonathan Ventura, Luis Vera, Tom Vercauteren, C. A. Verrastro, Lasitha Vidyaratne, Veronica Vilaplana, Ajeet Vivekanandan, Qian Wang, Chiatse J. Wang, Wei-Chung Wang, Duo Wang, Ruixuan Wang, Yuanyuan Wang, Chunliang Wang, Guotai Wang, Ning Wen, Xin Wen, Leon Weninger, Wolfgang Wick, Shaocheng Wu, Qiang Wu, Yihong Wu, Yong Xia, Yanwu Xu, Xiaowen Xu, Peiyuan Xu, Tsai-Ling Yang, Xiaoping Yang, Hao-Yu Yang, Junlin Yang, Haojin Yang, Guang Yang, Hongdou Yao, Xujiong Ye, Changchang Yin, Brett Young-Moxon, Jinhua Yu, Xiangyu Yue, Songtao Zhang, Angela Zhang, Kun Zhang, Xue-jie Zhang, Lichi Zhang, Xiaoyue Zhang, Yazhuo Zhang, Lei Zhang, Jian-Guo Zhang, Xiang Zhang, Tianhao Zhang, Sicheng Zhao, Yu Zhao, Xiaomei Zhao, Liang Zhao, Yefeng Zheng, Liming Zhong, Chenhong Zhou, Xiaobing Zhou, Fan Zhou, Hongtu Zhu, Jin Zhu, Ying Zhuge, Weiwei Zong, Jayashree Kalpathy-Cramer, Keyvan Farahani, Christos Davatzikos, Koen van Leemput, Bjoern Menze

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.

Brain Tumor Segmentation Survival Prediction +1

Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning

no code implementations17 Sep 2018 Jun Feng, Heng Li, Minlie Huang, Shichen Liu, Wenwu Ou, Zhirong Wang, Xiaoyan Zhu

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

Minimap2: pairwise alignment for nucleotide sequences

3 code implementations4 Aug 2017 Heng Li

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.

Towards Better Understanding of Artifacts in Variant Calling from High-Coverage Samples

2 code implementations3 Apr 2014 Heng Li

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.

Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM

17 code implementations16 Mar 2013 Heng Li

Summary: BWA-MEM is a new alignment algorithm for aligning sequence reads or long query sequences against a large reference genome such as human.

3D Object Reconstruction From A Single Image Genomics

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