no code implementations • ICML 2020 • Tung-Che Liang, Zhanwei Zhong, Yaas Bigdeli, Tsung-Yi Ho, Richard Fair, Krishnendu Chakrabarty
We present and investigate a novel application domain for deep reinforcement learning (RL): droplet routing on digital microfluidic biochips (DMFBs).
1 code implementation • 14 May 2024 • Qingpeng Kong, Ching-Hao Chiu, Dewen Zeng, Yu-Jen Chen, Tsung-Yi Ho, Jingtong Hu, Yiyu Shi
Numerous studies have revealed that deep learning-based medical image classification models may exhibit bias towards specific demographic attributes, such as race, gender, and age.
no code implementations • 9 May 2024 • Fangzhou Wang, Qijing Wang, Lilas Alrahis, Bangqi Fu, Shui Jiang, Xiaopeng Zhang, Ozgur Sinanoglu, Tsung-Yi Ho, Evangeline F. Y. Young, Johann Knechtel
In this work, we proactively and systematically protect the physical layouts of ICs against post-design insertion of Trojans.
1 code implementation • 21 Mar 2024 • Yi-Shan Lan, Pin-Yu Chen, Tsung-Yi Ho
In this paper, we propose novel semantic data augmentation methods, Novel Augmentation of New Node Attributes (NaNa), and Molecular Interactions and Geometric Upgrading (MiGu) to incorporate backbone chemical and side-chain biophysical information into protein classification tasks and a co-embedding residual learning framework.
no code implementations • 8 Mar 2024 • Muxi Chen, Yi Liu, Jian Yi, Changran Xu, Qiuxia Lai, Hongliang Wang, Tsung-Yi Ho, Qiang Xu
In this paper, we present an empirical study introducing a nuanced evaluation framework for text-to-image (T2I) generative models, applied to human image synthesis.
no code implementations • 1 Mar 2024 • Xiaomeng Hu, Pin-Yu Chen, Tsung-Yi Ho
Large Language Models (LLMs) are becoming a prominent generative AI tool, where the user enters a query and the LLM generates an answer.
no code implementations • 20 Feb 2024 • Hao-Wei Chung, Ching-Hao Chiu, Yu-Jen Chen, Yiyu Shi, Tsung-Yi Ho
Fairness has become increasingly pivotal in machine learning for high-risk applications such as machine learning in healthcare and facial recognition.
no code implementations • 16 Jan 2024 • Ching-Hao Chiu, Yu-Jen Chen, Yawen Wu, Yiyu Shi, Tsung-Yi Ho
To overcome this, we propose a method enabling fair predictions for sensitive attributes during the testing phase without using such information during training.
2 code implementations • 29 Nov 2023 • Yijun Yang, Ruiyuan Gao, Xiaosen Wang, Tsung-Yi Ho, Nan Xu, Qiang Xu
In recent years, Text-to-Image (T2I) models have seen remarkable advancements, gaining widespread adoption.
no code implementations • 28 Nov 2023 • Ming-Yu Chung, Sheng-Yen Chou, Chia-Mu Yu, Pin-Yu Chen, Sy-Yen Kuo, Tsung-Yi Ho
Dataset distillation offers a potential means to enhance data efficiency in deep learning.
1 code implementation • 27 Nov 2023 • Shengwei An, Sheng-Yen Chou, Kaiyuan Zhang, QiuLing Xu, Guanhong Tao, Guangyu Shen, Siyuan Cheng, Shiqing Ma, Pin-Yu Chen, Tsung-Yi Ho, Xiangyu Zhang
Diffusion models (DM) have become state-of-the-art generative models because of their capability to generate high-quality images from noises without adversarial training.
1 code implementation • 12 Oct 2023 • Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Sijia Liu, Tsung-Yi Ho
To bridge this gap, we propose AutoVP, an end-to-end expandable framework for automating VP design choices, along with 12 downstream image-classification tasks that can serve as a holistic VP-performance benchmark.
1 code implementation • 29 Jun 2023 • Hao-Lun Sun, Lei Hsiung, Nandhini Chandramoorthy, Pin-Yu Chen, Tsung-Yi Ho
To address this challenge, we introduce NeuralFuse, a novel add-on module that addresses the accuracy-energy tradeoff in low-voltage regimes by learning input transformations to generate error-resistant data representations.
1 code implementation • 26 Jun 2023 • Yu-Jen Chen, Xinrong Hu, Yiyu Shi, Tsung-Yi Ho
Magnetic resonance imaging (MRI) is commonly used for brain tumor segmentation, which is critical for patient evaluation and treatment planning.
no code implementations • 26 Jun 2023 • Ching-Hao Chiu, Hao-Wei Chung, Yu-Jen Chen, Yiyu Shi, Tsung-Yi Ho
Fairness has become increasingly pivotal in medical image recognition.
1 code implementation • NeurIPS 2023 • Sheng-Yen Chou, Pin-Yu Chen, Tsung-Yi Ho
This paper presents a unified backdoor attack framework (VillanDiffusion) to expand the current scope of backdoor analysis for DMs.
1 code implementation • 8 Jun 2023 • Yu-Jen Chen, Yiyu Shi, Tsung-Yi Ho
Magnetic resonance imaging (MRI) is a commonly used technique for brain tumor segmentation, which is critical for evaluating patients and planning treatment.
1 code implementation • 6 Jun 2023 • Xinrong Hu, Yu-Jen Chen, Tsung-Yi Ho, Yiyu Shi
Recent advances in denoising diffusion probabilistic models have shown great success in image synthesis tasks.
no code implementations • 19 Apr 2023 • Zaitang Li, Pin-Yu Chen, Tsung-Yi Ho
Formally, GREAT Score carries the physical meaning of a global statistic capturing a mean certified attack-proof perturbation level over all samples drawn from a generative model.
no code implementations • 8 Jan 2023 • Ching-Hao Chiu, Hao-Wei Chung, Yu-Jen Chen, Yiyu Shi, Tsung-Yi Ho
Fairness has become increasingly pivotal in facial recognition.
1 code implementation • CVPR 2023 • Sheng-Yen Chou, Pin-Yu Chen, Tsung-Yi Ho
To gain a better understanding of the limitations and potential risks, this paper presents the first study on the robustness of diffusion models against backdoor attacks.
1 code implementation • 29 Nov 2022 • Lei Hsiung, Yung-Chen Tang, Pin-Yu Chen, Tsung-Yi Ho
With the advancement of deep learning technology, neural networks have demonstrated their excellent ability to provide accurate predictions in many tasks.
no code implementations • 15 Nov 2022 • Fangzhou Wang, Qijing Wang, Bangqi Fu, Shui Jiang, Xiaopeng Zhang, Lilas Alrahis, Ozgur Sinanoglu, Johann Knechtel, Tsung-Yi Ho, Evangeline F. Y. Young
In this work, we proactively and systematically harden the physical layouts of ICs against post-design insertion of Trojans.
no code implementations • 23 Sep 2022 • Yung-Chen Tang, Pin-Yu Chen, Tsung-Yi Ho
Neural network calibration is an essential task in deep learning to ensure consistency between the confidence of model prediction and the true correctness likelihood.
no code implementations • 4 Sep 2022 • Yu-Jen Chen, Wei-Hsiang Shen, Hao-Wei Chung, Ching-Hao Chiu, Da-Cheng Juan, Tsung-Ying Ho, Chi-Tung Cheng, Meng-Lin Li, Tsung-Yi Ho
Medical report generation is a challenging task since it is time-consuming and requires expertise from experienced radiologists.
no code implementations • 31 Aug 2022 • Zhiyuan He, Yijun Yang, Pin-Yu Chen, Qiang Xu, Tsung-Yi Ho
Empowered by the robust relation net built on SSL, we found that BEYOND outperforms baselines in terms of both detection ability and speed.
1 code implementation • 16 Jul 2022 • Lei Hsiung, Yun-Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho
Prior literature on adversarial attack methods has mainly focused on attacking with and defending against a single threat model, e. g., perturbations bounded in Lp ball.
1 code implementation • CVPR 2023 • Lei Hsiung, Yun-Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho
We then propose generalized adversarial training (GAT) to extend model robustness from $\ell_{p}$-ball to composite semantic perturbations, such as the combination of Hue, Saturation, Brightness, Contrast, and Rotation.
no code implementations • 23 Oct 2021 • Yu-Jen Chen, Yen-Jung Chang, Shao-Cheng Wen, Yiyu Shi, Xiaowei Xu, Tsung-Yi Ho, Meiping Huang, Haiyun Yuan, Jian Zhuang
Medical images may contain various types of artifacts with different patterns and mixtures, which depend on many factors such as scan setting, machine condition, patients' characteristics, surrounding environment, etc.
no code implementations • ICML Workshop AML 2021 • Yun-Yun Tsai, Lei Hsiung, Pin-Yu Chen, Tsung-Yi Ho
We then propose generalized adversarial training (GAT) to extend model robustness from $\ell_{p}$ norm to composite semantic perturbations, such as Hue, Saturation, Brightness, Contrast, and Rotation.
no code implementations • 4 Nov 2020 • Shao-Cheng Wen, Yu-Jen Chen, Zihao Liu, Wujie Wen, Xiaowei Xu, Yiyu Shi, Tsung-Yi Ho, Qianjun Jia, Meiping Huang, Jian Zhuang
Deep learning had already demonstrated its power in medical images, including denoising, classification, segmentation, etc.
no code implementations • ICML 2020 • Yun-Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho
Current transfer learning methods are mainly based on finetuning a pretrained model with target-domain data.
BIG-bench Machine Learning Diabetic Retinopathy Detection +1