Speech Emotion Classification on a Riemannian Manifold. - Chengxi Ye; Jia Liu 030; Chun Chen 001; Mingli Song; Jiajun Bu (PCM, 2008)

Viewpoint Independent Vehicle Speed Estimation From Uncalibrated Traffic Surveillance Cameras. - Haili Mao; Chengxi Ye; Mingli Song; Jiajun Bu; Na Li (SMC, 2009)

SparseAssembler: de novo Assembly with the Sparse de Bruijn Graph - Chengxi Ye; Zhanshan (Sam) Ma; Charles H. Cannon; Mihai Pop; Douglas W. Yu (CoRR, 2011)

SparseAssembler2: Sparse k-mer Graph for Memory Efficient Genome Assembly - Chengxi Ye; Charles H. Cannon; Zhanshan (Sam) Ma; Douglas W. Yu; Mihai Pop (CoRR, 2011)

Exploiting sparseness in de novo genome assembly. - Chengxi Ye; Zhanshan (Sam) Ma; Charles H. Cannon; Mihai Pop; Douglas W. Yu (BMC Bioinform., 2012)

Spectral Graph Cut from a Filtering Point of View - Chengxi Ye; Yuxu Lin; Mingli Song; Chun Chen 001; David W. Jacobs (CoRR, 2012)

Sparse Norm Filtering - Chengxi Ye; Dacheng Tao; Mingli Song; David W. Jacobs; Min Wu (CoRR, 2013)

BlindCall: ultra-fast base-calling of high-throughput sequencing data by blind deconvolution. - Chengxi Ye; Chiaowen Hsiao; Héctor Corrada Bravo (Bioinform., 2014)

LightNet: A Versatile, Standalone Matlab-based Environment for Deep Learning. - Chengxi Ye; Chen Zhao 009; Yezhou Yang; Cornelia Fermüller; Yiannis Aloimonos (ACM Multimedia, 2016)

What Can I Do Around Here? Deep Functional Scene Understanding for Cognitive Robots. - Chengxi Ye; Yezhou Yang; Cornelia Fermüller; Yiannis Aloimonos (CoRR, 2016)

What can i do around here? Deep functional scene understanding for cognitive robots. - Chengxi Ye; Yezhou Yang; Ren Mao; Cornelia Fermüller; Yiannis Aloimonos (ICRA, 2017)

On the Importance of Consistency in Training Deep Neural Networks. - Chengxi Ye; Yezhou Yang; Cornelia Fermüller; Yiannis Aloimonos (CoRR, 2017)

Evenly Cascaded Convolutional Networks. - Chengxi Ye; Chinmaya Devaraj; Michael Maynord; Cornelia Fermüller; Yiannis Aloimonos (IEEE BigData, 2018)

Unsupervised Learning of Dense Optical Flow and Depth from Sparse Event Data. - Chengxi Ye; Anton Mitrokhin; Chethan Parameshwara; Cornelia Fermüller; James A. Yorke; Yiannis Aloimonos (CoRR, 2018)

EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras. - Anton Mitrokhin; Chengxi Ye; Cornelia Fermüller; Yiannis Aloimonos; Tobi Delbruck (IROS, 2019)

Learning of Dense optical Flow, motion and depth, from Sparse Event Cameras. - Chengxi Ye (2019)

Network Deconvolution. - Chengxi Ye; Matthew Evanusa; Hua He; Anton Mitrokhin; Tom Goldstein; James A. Yorke; Cornelia Fermüller; Yiannis Aloimonos (ICLR, 2020)

Unsupervised Learning of Dense Optical Flow, Depth and Egomotion with Event-Based Sensors. - Chengxi Ye; Anton Mitrokhin; Cornelia Fermüller; James A. Yorke; Yiannis Aloimonos (IROS, 2020)

Exploiting Invariance in Training Deep Neural Networks. - Chengxi Ye; Xiong Zhou; Tristan McKinney; Yanfeng Liu; Qinggang Zhou; Fedor Zhdanov (AAAI, 2022)

MobileNetV4: Universal Models for the Mobile Ecosystem. - Danfeng Qin; Chas Leichner; Manolis Delakis; Marco Fornoni; Shixin Luo; Fan Yang; Weijun Wang; Colby R. Banbury; Chengxi Ye; Berkin Akin; Vaibhav Aggarwal; Tenghui Zhu; et al. (ECCV (40), 2024)

Robust Training of Neural Networks at Arbitrary Precision and Sparsity. - Chengxi Ye; Grace Chu; Yanfeng Liu; Yichi Zhang; Lukasz Lew; Andrew G. Howard (CoRR, 2024)