Search Results for author: Si-Qi Liu

Found 27 papers, 8 papers with code

Inherent Consistent Learning for Accurate Semi-supervised Medical Image Segmentation

2 code implementations24 Mar 2023 Ye Zhu, Jie Yang, Si-Qi Liu, Ruimao Zhang

Semi-supervised medical image segmentation has attracted much attention in recent years because of the high cost of medical image annotations.

Image Segmentation Segmentation +2

Automated detection and quantification of COVID-19 airspace disease on chest radiographs: A novel approach achieving radiologist-level performance using a CNN trained on digital reconstructed radiographs (DRRs) from CT-based ground-truth

no code implementations13 Aug 2020 Eduardo Mortani Barbosa Jr., Warren B. Gefter, Rochelle Yang, Florin C. Ghesu, Si-Qi Liu, Boris Mailhe, Awais Mansoor, Sasa Grbic, Sebastian Piat, Guillaume Chabin, Vishwanath R S., Abishek Balachandran, Sebastian Vogt, Valentin Ziebandt, Steffen Kappler, Dorin Comaniciu

Purpose: To leverage volumetric quantification of airspace disease (AD) derived from a superior modality (CT) serving as ground truth, projected onto digitally reconstructed radiographs (DRRs) to: 1) train a convolutional neural network to quantify airspace disease on paired CXRs; and 2) compare the DRR-trained CNN to expert human readers in the CXR evaluation of patients with confirmed COVID-19.

dm_control: Software and Tasks for Continuous Control

2 code implementations22 Jun 2020 Yuval Tassa, Saran Tunyasuvunakool, Alistair Muldal, Yotam Doron, Piotr Trochim, Si-Qi Liu, Steven Bohez, Josh Merel, Tom Erez, Timothy Lillicrap, Nicolas Heess

The dm_control software package is a collection of Python libraries and task suites for reinforcement learning agents in an articulated-body simulation.

Continuous Control reinforcement-learning +1

MLOS: An Infrastructure for Automated Software Performance Engineering

no code implementations1 Jun 2020 Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Si-Qi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu

In this paper we present: MLOS, an ML-powered infrastructure and methodology to democratize and automate Software Performance Engineering.

Sentiment Analysis of Yelp Reviews: A Comparison of Techniques and Models

1 code implementation15 Apr 2020 Si-Qi Liu

We use over 350, 000 Yelp reviews on 5, 000 restaurants to perform an ablation study on text preprocessing techniques.

BIG-bench Machine Learning regression +2

Graph Attention Network based Pruning for Reconstructing 3D Liver Vessel Morphology from Contrasted CT Images

no code implementations18 Mar 2020 Donghao Zhang, Si-Qi Liu, Shikha Chaganti, Eli Gibson, Zhoubing Xu, Sasa Grbic, Weidong Cai, Dorin Comaniciu

In this paper, we propose a framework for liver vessel morphology reconstruction using both a fully convolutional neural network and a graph attention network.

3D Reconstruction Decision Making +2

No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting with Adversarial Attacks

no code implementations8 Mar 2020 Si-Qi Liu, Arnaud Arindra Adiyoso Setio, Florin C. Ghesu, Eli Gibson, Sasa Grbic, Bogdan Georgescu, Dorin Comaniciu

To make the network more robust to unanticipated noise perturbations, we use PGD to search for noise patterns that can trigger the network to give over-confident mistakes.

Adversarial Attack Lung Nodule Detection

Event Outlier Detection in Continuous Time

1 code implementation19 Dec 2019 Si-Qi Liu, Milos Hauskrecht

In this work, we study and develop methods for detecting outliers in continuous-time event sequences, including unexpected absence and unexpected occurrences of events.

Outlier Detection Point Processes +2

Nonparametric Regressive Point Processes Based on Conditional Gaussian Processes

no code implementations NeurIPS 2019 Si-Qi Liu, Milos Hauskrecht

``Regressive point processes'' refer to point processes that directly model the dependency between an event and any past event, an example of which is a Hawkes process.

Gaussian Processes Point Processes

Multi-Sensor 3D Object Box Refinement for Autonomous Driving

no code implementations11 Sep 2019 Peiliang Li, Si-Qi Liu, Shaojie Shen

We propose a 3D object detection system with multi-sensor refinement in the context of autonomous driving.

3D Object Detection Autonomous Driving +2

Deep Reinforcement Learning for Clinical Decision Support: A Brief Survey

no code implementations22 Jul 2019 Si-Qi Liu, Kee Yuan Ngiam, Mengling Feng

Owe to the recent advancements in Artificial Intelligence especially deep learning, many data-driven decision support systems have been implemented to facilitate medical doctors in delivering personalized care.

reinforcement-learning Reinforcement Learning (RL)

Emergent Coordination Through Competition

no code implementations ICLR 2019 Si-Qi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel

We study the emergence of cooperative behaviors in reinforcement learning agents by introducing a challenging competitive multi-agent soccer environment with continuous simulated physics.

Continuous Control Reinforcement Learning (RL)

Class-Aware Adversarial Lung Nodule Synthesis in CT Images

no code implementations28 Dec 2018 Jie Yang, Si-Qi Liu, Sasa Grbic, Arnaud Arindra Adiyoso Setio, Zhoubing Xu, Eli Gibson, Guillaume Chabin, Bogdan Georgescu, Andrew F. Laine, Dorin Comaniciu

Synthesizing the objects of interests, such as lung nodules, in medical images based on the distribution of annotated datasets can be helpful for improving the supervised learning tasks, especially when the datasets are limited by size and class balance.

Binary Classification General Classification

Detection of Abnormal Input-Output Associations

no code implementations3 Aug 2017 Charmgil Hong, Si-Qi Liu, Milos Hauskrecht

We study a novel outlier detection problem that aims to identify abnormal input-output associations in data, whose instances consist of multi-dimensional input (context) and output (responses) pairs.

Outlier Detection Relation

Improved Image Captioning via Policy Gradient optimization of SPIDEr

2 code implementations ICCV 2017 Si-Qi Liu, Zhenhai Zhu, Ning Ye, Sergio Guadarrama, Kevin Murphy

Finally, we show that using our PG method we can optimize any of the metrics, including the proposed SPIDEr metric which results in image captions that are strongly preferred by human raters compared to captions generated by the same model but trained to optimize MLE or the COCO metrics.

Image Captioning

Morphometry-Based Longitudinal Neurodegeneration Simulation with MR Imaging

no code implementations24 Aug 2015 Si-Qi Liu, Sidong Liu, Sonia Pujol, Ron Kikinis, Dagan Feng, Michael Fulham, Weidong Cai

We present a longitudinal MR simulation framework which simulates the future neurodegenerative progression by outputting the predicted follow-up MR image and the voxel-based morphometry (VBM) map.

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