Search Results for author: Chunhao Wang

Found 9 papers, 1 papers with code

A Neural Ordinary Differential Equation Model for Visualizing Deep Neural Network Behaviors in Multi-Parametric MRI based Glioma Segmentation

no code implementations1 Mar 2022 Zhenyu Yang, Zongsheng Hu, Hangjie Ji, Kyle Lafata, Scott Floyd, Fang-Fang Yin, Chunhao Wang

Methods: By hypothesizing that deep feature extraction can be modeled as a spatiotemporally continuous process, we designed a novel deep learning model, neural ODE, in which deep feature extraction was governed by an ODE without explicit expression.

A Radiomics-Boosted Deep-Learning Model for COVID-19 and Non-COVID-19 Pneumonia Classification Using Chest X-ray Image

no code implementations19 Jul 2021 Zongsheng Hu, Zhenyu Yang, Kyle J. Lafata, Fang-Fang Yin, Chunhao Wang

To develop a deep-learning model that integrates radiomics analysis for enhanced performance of COVID-19 and Non-COVID-19 pneumonia detection using chest X-ray image, two deep-learning models were trained based on a pre-trained VGG-16 architecture: in the 1st model, X-ray image was the sole input; in the 2nd model, X-ray image and 2 radiomic feature maps (RFM) selected by the saliency map analysis of the 1st model were stacked as the input.

Pneumonia Detection

Post-Radiotherapy PET Image Outcome Prediction by Deep Learning under Biological Model Guidance: A Feasibility Study of Oropharyngeal Cancer Application

no code implementations22 May 2021 Hangjie Ji, Kyle Lafata, Yvonne Mowery, David Brizel, Andrea L. Bertozzi, Fang-Fang Yin, Chunhao Wang

With break-down biological modeling components, the outcome image predictions could be used in adaptive radiotherapy decision-making to optimize personalized plans for the best outcome in the future.

Decision Making Time Series

Sublinear classical and quantum algorithms for general matrix games

no code implementations11 Dec 2020 Tongyang Li, Chunhao Wang, Shouvanik Chakrabarti, Xiaodi Wu

We give a sublinear classical algorithm that can interpolate smoothly between these two cases: for any fixed $q\in (1, 2]$, we solve the matrix game where $\mathcal{X}$ is a $\ell_{q}$-norm unit ball within additive error $\epsilon$ in time $\tilde{O}((n+d)/{\epsilon^{2}})$.

Sampling-based sublinear low-rank matrix arithmetic framework for dequantizing quantum machine learning

no code implementations14 Oct 2019 Nai-Hui Chia, András Gilyén, Tongyang Li, Han-Hsuan Lin, Ewin Tang, Chunhao Wang

Motivated by quantum linear algebra algorithms and the quantum singular value transformation (SVT) framework of Gily\'en et al. [STOC'19], we develop classical algorithms for SVT that run in time independent of input dimension, under suitable quantum-inspired sampling assumptions.

Recommendation Systems

Quantum-inspired sublinear algorithm for solving low-rank semidefinite programming

no code implementations10 Jan 2019 Nai-Hui Chia, Tongyang Li, Han-Hsuan Lin, Chunhao Wang

In this paper, we present a proof-of-principle sublinear-time algorithm for solving SDPs with low-rank constraints; specifically, given an SDP with $m$ constraint matrices, each of dimension $n$ and rank $r$, our algorithm can compute any entry and efficient descriptions of the spectral decomposition of the solution matrix.

Quantum-inspired sublinear classical algorithms for solving low-rank linear systems

no code implementations12 Nov 2018 Nai-Hui Chia, Han-Hsuan Lin, Chunhao Wang

Our algorithms are inspired by the HHL quantum algorithm for solving linear systems and the recent breakthrough by Tang of dequantizing the quantum algorithm for recommendation systems.

Recommendation Systems

Efficient Quantum Algorithms for Simulating Lindblad Evolution

no code implementations30 Dec 2016 Richard Cleve, Chunhao Wang

We consider the natural generalization of the Schr\"{o}dinger equation to Markovian open system dynamics: the so-called the Lindblad equation.

Quantum Physics

Near-linear constructions of exact unitary 2-designs

1 code implementation19 Jan 2015 Richard Cleve, Debbie Leung, Li Liu, Chunhao Wang

A unitary 2-design can be viewed as a quantum analogue of a 2-universal hash function: it is indistinguishable from a truly random unitary by any procedure that queries it twice.

Quantum Physics

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