no code implementations • 18 Mar 2024 • Xufeng Yao, Haoyang Li, Tsz Ho Chan, Wenyi Xiao, Mingxuan Yuan, Yu Huang, Lei Chen, Bei Yu
In the domain of chip design, Hardware Description Languages (HDLs) play a pivotal role.
no code implementations • 6 Mar 2024 • Gen Li, Yu Huang, Timofey Efimov, Yuting Wei, Yuejie Chi, Yuxin Chen
Score-based diffusion models, while achieving remarkable empirical performance, often suffer from low sampling speed, due to extensive function evaluations needed during the sampling phase.
no code implementations • 4 Mar 2024 • Yu Huang, Zixin Wen, Yuejie Chi, Yingbin Liang
Masked image modeling (MIM), which predicts randomly masked patches from unmasked ones, has emerged as a promising approach in self-supervised vision pretraining.
no code implementations • 22 Feb 2024 • Jiliang Li, Yifan Zhang, Zachary Karas, Collin McMillan, Kevin Leach, Yu Huang
Furthermore, alignment between model and human foci in this setting does not seem to dictate the quality of the LLM-generated summaries.
1 code implementation • 21 Feb 2024 • Yifan Zhang, Jiliang Li, Zachary Karas, Aakash Bansal, Toby Jia-Jun Li, Collin McMillan, Kevin Leach, Yu Huang
Neural code summarization leverages deep learning models to automatically generate brief natural language summaries of code snippets.
no code implementations • 3 Feb 2024 • Aokun Chen, Qian Li, Yu Huang, Yongqiu Li, Yu-Neng Chuang, Xia Hu, Serena Guo, Yonghui Wu, Yi Guo, Jiang Bian
We constructed an interactive knowledge map to disseminate our study results.
no code implementations • 3 Feb 2024 • Zehua Pei, Hui-Ling Zhen, Mingxuan Yuan, Yu Huang, Bei Yu
In this work, we propose a Verilog generation framework, BetterV, which fine-tunes the large language models (LLMs) on processed domain-specific datasets and incorporates generative discriminators for guidance on particular design demands.
no code implementations • 29 Nov 2023 • Lukas Hirsch, Yu Huang, Hernan A. Makse, Danny F. Martinez, Mary Hughes, Sarah Eskreis-Winkler, Katja Pinker, Elizabeth Morris, Lucas C. Parra, Elizabeth J. Sutton
Reevaluating these regions in 10% of all cases with higher AI-predicted risk could have resulted in up to 33% early detections by a radiologist.
no code implementations • 20 Nov 2023 • Yu Huang, Yue Chen, Zhu Li
Since DARPA Grand Challenges (rural) in 2004/05 and Urban Challenges in 2007, autonomous driving has been the most active field of AI applications.
no code implementations • 10 Oct 2023 • Siting Li, Chenzhuang Du, Yue Zhao, Yu Huang, Hang Zhao
With the growing success of multi-modal learning, research on the robustness of multi-modal models, especially when facing situations with missing modalities, is receiving increased attention.
no code implementations • 8 Oct 2023 • Yu Huang, Yuan Cheng, Yingbin Liang
For data with balanced features, we establish the finite-time convergence guarantee with near-zero prediction error by navigating our analysis over two phases of the training dynamics of the attention map.
no code implementations • 5 Sep 2023 • Yu Huang, Jingchuan Guo, William T Donahoo, Zhengkang Fan, Ying Lu, Wei-Han Chen, Huilin Tang, Lori Bilello, Elizabeth A Shenkman, Jiang Bian
Background: Racial and ethnic minority groups and individuals facing social disadvantages, which often stem from their social determinants of health (SDoH), bear a disproportionate burden of type 2 diabetes (T2D) and its complications.
no code implementations • 23 Jun 2023 • Yu Huang, Yue Chen, Zijiang Yang
Since DARPA started Grand Challenges in 2004 and Urban Challenges in 2007, autonomous driving has been the most active field of AI applications.
1 code implementation • NeurIPS 2023 • Sungduk Yu, Walter Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus Christopher Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles I Stern, Tom Beucler, Bryce Harrop, Benjamin R Hillman, Andrea Jenney, Savannah Ferretti, Nana Liu, Anima Anandkumar, Noah D Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C Bader, Pierre Baldi, Elizabeth Barnes, Christopher Bretherton, Peter Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David Randall, Sara Shamekh, Mark A Taylor, Nathan Urban, Janni Yuval, Guang Zhang, Michael Pritchard
The dataset is global in coverage, spans multiple years at high sampling frequency, and is designed such that resulting emulators are compatible with downstream coupling into operational climate simulators.
1 code implementation • 25 May 2023 • Hanchong Zhang, Jieyu Li, Lu Chen, Ruisheng Cao, Yunyan Zhang, Yu Huang, Yefeng Zheng, Kai Yu
Furthermore, we present CSS, a large-scale CrosS-Schema Chinese text-to-SQL dataset, to carry on corresponding studies.
no code implementations • 4 Mar 2023 • Hui-Ling Zhen, Naixing Wang, Junhua Huang, Xinyue Huang, Mingxuan Yuan, Yu Huang
(2) Conflict-driven implication and justification have been applied to increase decision accuracy and solving efficiency.
no code implementations • 21 Jan 2023 • Angzhi Fan, Yu Huang, Fei Xu, Sthitie Bom
The semiconductor industry is one of the most technology-evolving and capital-intensive market sectors.
no code implementations • 11 Oct 2022 • Yifan Zhang, Chen Huang, Yueke Zhang, Kevin Cao, Scott Thomas Andersen, Huajie Shao, Kevin Leach, Yu Huang
To the best of our knowledge, COMBO is the first language representation model that incorporates source code, binary code, and comments into contrastive code representation learning and unifies multiple tasks for binary code analysis.
no code implementations • 19 Jul 2022 • Xuan Chen, Fei Ji, Miaowen Wen, Yu Huang, Yuankun Tang, Andrew W. Eckford
In this paper, we propose a novel inter-symbol interference (ISI) mitigation scheme for molecular communication via diffusion (MCvD) systems with the optimal detection interval.
no code implementations • 18 Jun 2022 • Yu Huang, Yingbin Liang, Longbo Huang
Despite the superior empirical success of deep meta-learning, theoretical understanding of overparameterized meta-learning is still limited.
1 code implementation • 7 Jun 2022 • Zhengyuan Shi, Min Li, Sadaf Khan, Liuzheng Wang, Naixing Wang, Yu Huang, Qiang Xu
Unlike previous learning-based solutions that formulate the TPI task as a supervised-learning problem, we train a novel DRL agent, instantiated as the combination of a graph neural network (GNN) and a Deep Q-Learning network (DQN), to maximize the test coverage improvement.
no code implementations • 3 Jun 2022 • Ali Muhamed Ali, Hanqi Zhuang, Yu Huang, Ali K. Ibrahim, Ali Salem Altaher, Laurent Chérubin
The caveat of this approach is that measurements are used only once, at the time of the prediction.
no code implementations • 24 Mar 2022 • Bowen Wang, Guibao Shen, Dong Li, Jianye Hao, Wulong Liu, Yu Huang, HongZhong Wu, Yibo Lin, Guangyong Chen, Pheng Ann Heng
Precise congestion prediction from a placement solution plays a crucial role in circuit placement.
no code implementations • 23 Mar 2022 • Yu Xiang, Yu Huang, Haodong Xu, Guangbo Zhang, Wenyong Wang
The identification of pedestrians using radar micro-Doppler signatures has become a hot topic in recent years.
no code implementations • 23 Mar 2022 • Yu Huang, Junyang Lin, Chang Zhou, Hongxia Yang, Longbo Huang
Recently, it has been observed that the best uni-modal network outperforms the jointly trained multi-modal network, which is counter-intuitive since multiple signals generally bring more information.
1 code implementation • 26 Nov 2021 • Min Li, Zhengyuan Shi, Zezhong Wang, Weiwei Zhang, Yu Huang, Qiang Xu
The proposed GA-guided XORNets also allows reducing the number of control bits, and the total testing time decreases by 20. 78% on average and up to 47. 09% compared to the existing design without sacrificing test coverage.
1 code implementation • 26 Nov 2021 • Min Li, Sadaf Khan, Zhengyuan Shi, Naixing Wang, Yu Huang, Qiang Xu
We propose DeepGate, a novel representation learning solution that effectively embeds both logic function and structural information of a circuit as vectors on each gate.
no code implementations • 12 Nov 2021 • Jaswanth Yella, Chao Zhang, Sergei Petrov, Yu Huang, Xiaoye Qian, Ali A. Minai, Sthitie Bom
Over the last few decades, modern industrial processes have investigated several cost-effective methodologies to improve the productivity and yield of semiconductor manufacturing.
no code implementations • 12 Nov 2021 • Xiaoye Qian, Chao Zhang, Jaswanth Yella, Yu Huang, Ming-Chun Huang, Sthitie Bom
To understand how the proposed model works, the deep visualization approach is applied.
no code implementations • 12 Nov 2021 • Yu Huang, Chao Zhang, Jaswanth Yella, Sergei Petrov, Xiaoye Qian, Yufei Tang, Xingquan Zhu, Sthitie Bom
In the era of big data, data-driven based classification has become an essential method in smart manufacturing to guide production and optimize inspection.
1 code implementation • 10 Nov 2021 • Chao Zhang, Jaswanth Yella, Yu Huang, Xiaoye Qian, Sergei Petrov, Andrey Rzhetsky, Sthitie Bom
We demonstrate the challenges and effectiveness of modeling industrial big data by a Soft Sensing Transformer model on these data sets.
no code implementations • 7 Sep 2021 • Sergei Petrov, Chao Zhang, Jaswanth Yella, Yu Huang, Xiaoye Qian, Sthitie Bom
The scope of this challenge is to tackle the task of classifying soft sensing data with machine learning techniques.
no code implementations • 12 Aug 2021 • Yu Huang, James Li, Min Shi, Hanqi Zhuang, Xingquan Zhu, Laurent Chérubin, James VanZwieten, Yufei Tang
A spatio-temporal physics-coupled neural network (ST-PCNN) model is proposed to achieve three goals: (1) learning the underlying physics parameters, (2) transition of local information between spatio-temporal regions, and (3) forecasting future values for the dynamical system.
no code implementations • 11 Aug 2021 • Yu Huang, Yufei Tang, Xingquan Zhu, Min Shi, Ali Muhamed Ali, Hanqi Zhuang, Laurent Cherubin
To tackle these challenges, we advocate a spatio-temporal physics-coupled neural networks (ST-PCNN) model to learn the underlying physics of the dynamical system and further couple the learned physics to assist the learning of the recurring dynamics.
no code implementations • 28 Jul 2021 • Yu Huang, Gary G. Yen, Vincent S. Tseng
To the best of our knowledge, this is the first work focusing on solving the cardiovascular early classification problem based on varied-length ECG data.
no code implementations • NeurIPS 2021 • Yu Huang, Chenzhuang Du, Zihui Xue, Xuanyao Chen, Hang Zhao, Longbo Huang
The world provides us with data of multiple modalities.
no code implementations • 25 Jan 2021 • Mengbang Zou, Yu Huang, Weisi Guo
This approach is insufficient for dynamic networks with changing equilibrium and estimating the Region of Attraction(ROA) is needed.
Social and Information Networks
no code implementations • 22 Dec 2020 • Hui Chen, Hongkuan Zhang, Qian Wu, Yu Huang, Huy Nguyen, Emil Prodan, Xiaoming Zhou, Guoliang Huang
Synthetic dimensions can be rendered in the physical space and this has been achieved with photonics and cold atomic gases, however, little to no work has been succeeded in acoustics because acoustic wave-guides cannot be weakly coupled in a continuous fashion.
Mesoscale and Nanoscale Physics Classical Physics
no code implementations • 2 Dec 2020 • Weijie He, Xiaohao Mao, Chao Ma, Yu Huang, José Miguel Hernández-Lobato, Ting Chen
To address the challenge, we propose a non-RL Bipartite Scalable framework for Online Disease diAgnosis, called BSODA.
no code implementations • 21 Sep 2020 • Lukas Hirsch, Yu Huang, Shaojun Luo, Carolina Rossi Saccarelli, Roberto Lo Gullo, Isaac Daimiel Naranjo, Almir G. V. Bitencourt, Natsuko Onishi, Eun Sook Ko, Doris Leithner, Daly Avendano, Sarah Eskreis-Winkler, Mary Hughes, Danny F. Martinez, Katja Pinker, Krishna Juluru, Amin E. El-Rowmeim, Pierre Elnajjar, Elizabeth A. Morris, Hernan A. Makse, Lucas C Parra, Elizabeth J. Sutton
Conclusion: When trained on a sufficiently large dataset, the developed 3D U-Net performed as well as fellowship-trained radiologists in detailed 2D segmentation of breast cancers at routine clinical MRI.
1 code implementation • 21 Sep 2020 • Min Shi, David A. Wilson, Xingquan Zhu, Yu Huang, Yuan Zhuang, Jianxun Liu, Yufei Tang
In particular, Neural Architecture Search (NAS) has seen significant attention throughout the AutoML research community, and has pushed forward the state-of-the-art in a number of neural models to address grid-like data such as texts and images.
no code implementations • 4 Aug 2020 • Yu Huang, Yufei Tang, Hanqi Zhuang, James VanZwieten, Laurent Cherubin
According to the National Academies, a weekly forecast of velocity, vertical structure, and duration of the Loop Current (LC) and its eddies is critical for understanding the oceanography and ecosystem, and for mitigating outcomes of anthropogenic and natural disasters in the Gulf of Mexico (GoM).
no code implementations • 31 Jul 2020 • William B. Langdon, Westley Weimer, Justyna Petke, Erik Fredericks, Seongmin Lee, Emily Winter, Michail Basios, Myra B. Cohen, Aymeric Blot, Markus Wagner, Bobby R. Bruce, Shin Yoo, Simos Gerasimou, Oliver Krauss, Yu Huang, Michael Gerten
Following Prof. Mark Harman of Facebook's keynote and formal presentations (which are recorded in the proceedings) there was a wide ranging discussion at the eighth international Genetic Improvement workshop, GI-2020 @ ICSE (held as part of the 42nd ACM/IEEE International Conference on Software Engineering on Friday 3rd July 2020).
no code implementations • 10 Jun 2020 • Yu Huang, Yue Chen
Since DARPA Grand Challenges (rural) in 2004/05 and Urban Challenges in 2007, autonomous driving has been the most active field of AI applications.
no code implementations • 3 Sep 2019 • Ruqian Lu, Shengluan Hou, Chuanqing Wang, Yu Huang, Chaoqun Fei, Songmao Zhang
We have also shown that the knowledge based approach may be made more powerful by introducing grammar parsing and RST as inference engine.
no code implementations • 27 Jun 2019 • William B. Langdon, Westley Weimer, Christopher Timperley, Oliver Krauss, Zhen Yu Ding, Yiwei Lyu, Nicolas Chausseau, Eric Schulte, Shin Hwei Tan, Kevin Leach, Yu Huang, Gabin An
We report the discussion session at the sixth international Genetic Improvement workshop, GI-2019 @ ICSE, which was held as part of the 41st ACM/IEEE International Conference on Software Engineering on Tuesday 28th May 2019.
1 code implementation • 24 May 2019 • Lukas Hirsch, Yu Huang, Lucas C. Parra
The benefit of adding a TPM is generic in that it can boost the performance of established segmentation networks such as the DeepMedic and a UNet.