no code implementations • 23 Sep 2024 • Zihao Chen, Wenyong Wang, Yu Xiang
Manifold learning has been proven to be an effective method for capturing the implicitly intrinsic structure of non-Euclidean data, in which one of the primary challenges is how to maintain the distortion-free (isometry) of the data representations.
no code implementations • 13 Sep 2024 • Shu Cai, Zihao Chen, Ya-Feng Liu, Jun Zhang
Consider an integrated sensing and communication (ISAC) system where a base station (BS) employs a full-duplex radio to simultaneously serve multiple users and detect a target.
no code implementations • 1 Aug 2024 • Xinhan Di, Zihao Chen, Yunming Liang, Junjie Zheng, Yihua Wang, Chaofan Ding
Large-scale text-to-speech (TTS) models have made significant progress recently. However, they still fall short in the generation of Chinese dialectal speech.
no code implementations • 7 Jun 2024 • Zihao Chen, Zhili Xiao, Mahmoud Akl, Johannes Leugring, Omowuyi Olajide, Adil Malik, Nik Dennler, Chad Harper, Subhankar Bose, Hector A. Gonzalez, Jason Eshraghian, Riccardo Pignari, Gianvito Urgese, Andreas G. Andreou, Sadasivan Shankar, Christian Mayr, Gert Cauwenberghs, Shantanu Chakrabartty
We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using an annealing process that is governed by the physics of quantum mechanical tunneling using Fowler-Nordheim (FN).
no code implementations • 21 Feb 2024 • Zihao Chen, Johannes Leugering, Gert Cauwenberghs, Shantanu Chakrabartty
In this paper, we derive new theoretical lower bounds on energy dissipation when training AI systems using different LIM approaches.
no code implementations • 16 Oct 2023 • Zihao Chen, Yeshwanth Cherapanamjeri
We investigate the quantitative performance of affine-equivariant estimators for robust mean estimation.
no code implementations • 2 Sep 2023 • Zihao Chen, Xiao Chen, Yikang Liu, Eric Z. Chen, Terrence Chen, Shanhui Sun
Cardiac Magnetic Resonance imaging (CMR) is the gold standard for assessing cardiac function.
no code implementations • 22 May 2023 • Zihao Chen, Jia Lu, Xing-Ming Zhao, Haiyang Yu, Chunhe Li
Our results revealed the underlying mechanism for intermediate cell states governing the CAC, and identified new potential drug combinations to induce cancer adipogenesis.
no code implementations • 3 Apr 2023 • Zihao Chen, Xiaomeng Wang, Yuanjiang Huang, Tao Jia
More importantly, our model is used to test the correctness of the explanations generated by the post-hoc method, the results show that the post-hoc method is not always reliable.
1 code implementation • 19 Jan 2023 • Zihao Chen, Hisashi Handa, Kimiaki Shirahama
To overcome this, we propose a novel Japanese sentence representation framework, JCSE (derived from ``Contrastive learning of Sentence Embeddings for Japanese''), that creates training data by generating sentences and synthesizing them with sentences available in a target domain.
no code implementations • 17 Oct 2022 • Zihao Chen, Wenyong Wang, Sai Zou
The novel model enables VAE to adjust the parameter capacity to divide dependent and independent data features flexibly.
no code implementations • 7 Sep 2022 • Ziyan Lin, Zihao Chen
Magnetic Resonance Imaging (MRI) is important in clinic to produce high resolution images for diagnosis, but its acquisition time is long for high resolution images.
no code implementations • 15 Aug 2022 • Carole H. Sudre, Kimberlin Van Wijnen, Florian Dubost, Hieab Adams, David Atkinson, Frederik Barkhof, Mahlet A. Birhanu, Esther E. Bron, Robin Camarasa, Nish Chaturvedi, Yuan Chen, Zihao Chen, Shuai Chen, Qi Dou, Tavia Evans, Ivan Ezhov, Haojun Gao, Marta Girones Sanguesa, Juan Domingo Gispert, Beatriz Gomez Anson, Alun D. Hughes, M. Arfan Ikram, Silvia Ingala, H. Rolf Jaeger, Florian Kofler, Hugo J. Kuijf, Denis Kutnar, Minho Lee, Bo Li, Luigi Lorenzini, Bjoern Menze, Jose Luis Molinuevo, Yiwei Pan, Elodie Puybareau, Rafael Rehwald, Ruisheng Su, Pengcheng Shi, Lorna Smith, Therese Tillin, Guillaume Tochon, Helene Urien, Bas H. M. van der Velden, Isabelle F. van der Velpen, Benedikt Wiestler, Frank J. Wolters, Pinar Yilmaz, Marius de Groot, Meike W. Vernooij, Marleen de Bruijne
This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels.
no code implementations • 3 May 2022 • Zihao Chen, Yuhua Chen, Yibin Xie, Debiao Li, Anthony G. Christodoulou
Non-Cartesian sampling with subspace-constrained image reconstruction is a popular approach to dynamic MRI, but slow iterative reconstruction limits its clinical application.
no code implementations • ECCV 2020 • Xin Chen, Yawen Duan, Zewei Chen, Hang Xu, Zihao Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li
In spite of its remarkable progress, many algorithms are restricted to particular search spaces.
Ranked #14 on Neural Architecture Search on NAS-Bench-201, ImageNet-16-120 (Search time (s) metric)
1 code implementation • 10 Sep 2019 • Mostafa Elhoushi, Ye Henry Tian, Zihao Chen, Farhan Shafiq, Joey Yiwei Li
In our approach, we train the model from scratch (i. e., randomly initialized weights) with its original architecture for a small number of epochs, then the model is decomposed, and then continue training the decomposed model till the end.
1 code implementation • 30 May 2019 • Mostafa Elhoushi, Zihao Chen, Farhan Shafiq, Ye Henry Tian, Joey Yiwei Li
This family of neural network architectures (that use convolutional shifts and fully connected shifts) is referred to as DeepShift models.
no code implementations • 2 Dec 2016 • Zihao Chen, Luo Luo, Zhihua Zhang
Recently, there has been an increasing interest in designing distributed convex optimization algorithms under the setting where the data matrix is partitioned on features.
no code implementations • 31 Jan 2016 • Luo Luo, Zihao Chen, Zhihua Zhang, Wu-Jun Li
It incorporates the Hessian in the smooth part of the function and exploits multistage scheme to reduce the variance of the stochastic gradient.