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ORCIDDianbo Liu
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2020 – today
- 2024
[j7]Haoyue Sheng, Linrui Ma, Jean-Francois Samson, Dianbo Liu:
BarlowTwins-CXR: enhancing chest X-ray abnormality localization in heterogeneous data with cross-domain self-supervised learning. BMC Medical Informatics Decis. Mak. 24(1): 126 (2024)- [j6]Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu:
Physical Reasoning and Object Planning for Household Embodied Agents. Trans. Mach. Learn. Res. 2024 (2024) - [c12]Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi:
Unsupervised Concept Discovery Mitigates Spurious Correlations. ICML 2024 - [i47]Zarif Ikram, Ling Pan, Dianbo Liu:
Evolution Guided Generative Flow Networks. CoRR abs/2402.02186 (2024) - [i46]Haoyue Sheng, Linrui Ma, Jean-Francois Samson, Dianbo Liu:
BarlowTwins-CXR : Enhancing Chest X-Ray abnormality localization in heterogeneous data with cross-domain self-supervised learning. CoRR abs/2402.06499 (2024) - [i45]Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi:
Unsupervised Concept Discovery Mitigates Spurious Correlations. CoRR abs/2402.13368 (2024) - [i44]Anirudh Prabhakaran, YeKun Xiao, Ching-Yu Cheng, Dianbo Liu:
Improve Robustness of Eye Disease Detection by including Learnable Probabilistic Discrete Latent Variables into Machine Learning Models. CoRR abs/2402.16865 (2024) - [i43]Tianyi Zhang, Yu Cao, Dianbo Liu:
Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos. CoRR abs/2402.18888 (2024) - [i42]Jiawei Wu, Mingyuan Yan, Dianbo Liu:
VQSynery: Robust Drug Synergy Prediction With Vector Quantization Mechanism. CoRR abs/2403.03089 (2024) - [i41]Chunhui Li, Cheng-Hao Liu, Dianbo Liu, Qingpeng Cai, Ling Pan:
Bifurcated Generative Flow Networks. CoRR abs/2406.01901 (2024) - [i40]Hengguan Huang, Xing Shen, Songtao Wang, Dianbo Liu, Hao Wang:
Verbalized Probabilistic Graphical Modeling with Large Language Models. CoRR abs/2406.05516 (2024) - [i39]Meng Wang, Tian Lin, Aidi Lin, Kai Yu, Yuanyuan Peng, Lianyu Wang, Cheng Chen, Ke Zou, Huiyu Liang, Man Chen, Xue Yao, Meiqin Zhang, Binwei Huang, Chaoxin Zheng, Peixin Zhang, Wei Chen, Yilong Luo, Yifan Chen, Honghe Xia, Tingkun Shi, Qi Zhang, Jinming Guo, Xiaolin Chen, Jingcheng Wang, Yih Chung Tham, Dianbo Liu, Wendy Wong, Sahil Thakur, Beau Fenner, Danqi Fang, Siying Liu, Qingyun Liu, Yuqiang Huang, Hongqiang Zeng, Yanda Meng, Yukun Zhou, Zehua Jiang, Minghui Qiu, Changqing Zhang, Xinjian Chen, Sophia Y. Wang, Cecilia S. Lee, Lucia Sobrin, Carol Y. Cheung, Chi Pui Pang, Pearse A Keane, Ching-Yu Cheng, Haoyu Chen, Huazhu Fu:
Common and Rare Fundus Diseases Identification Using Vision-Language Foundation Model with Knowledge of Over 400 Diseases. CoRR abs/2406.09317 (2024) - [i38]Hang Chen, Sankepally Sainath Reddy, Ziwei Chen, Dianbo Liu:
Balance of Number of Embedding and their Dimensions in Vector Quantization. CoRR abs/2407.04939 (2024) - [i37]Xiaoye Wang, Nicole Xi Zhang, Hongyu He, Trang Nguyen, Kun-Hsing Yu, Hao Deng, Cynthia Brandt, Danielle S. Bitterman, Ling Pan, Ching-Yu Cheng, James Zou, Dianbo Liu:
Safety challenges of AI in medicine. CoRR abs/2409.18968 (2024) - [i36]Aidan Gilson, Xuguang Ai, Qianqian Xie, Sahana Srinivasan, Krithi Pushpanathan, Maxwell B. Singer, Jimin Huang, Hyunjae Kim, Erping Long, Peixing Wan, Luciano V. Del Priore, Lucila Ohno-Machado, Hua Xu, Dianbo Liu, Ron A. Adelman, Yih-Chung Tham, Qingyu Chen:
Language Enhanced Model for Eye (LEME): An Open-Source Ophthalmology-Specific Large Language Model. CoRR abs/2410.03740 (2024) - 2023
- [c11]Dianbo Liu, Alex Lamb, Xu Ji, Pascal Tikeng Notsawo Jr., Michael Mozer, Yoshua Bengio, Kenji Kawaguchi:
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness. AAAI 2023: 8825-8833 - [c10]Dianbo Liu, Vedant Shah, Oussama Boussif
, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Curtis Mozer, Nicolas Heess, Yoshua Bengio:
Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. ICLR 2023 - [c9]Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Chinenye Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio:
GFlowOut: Dropout with Generative Flow Networks. ICML 2023: 21715-21729 - [c8]Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio:
Reusable Slotwise Mechanisms. NeurIPS 2023 - [i35]Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio:
Reusable Slotwise Mechanisms. CoRR abs/2302.10503 (2023) - [i34]Dianbo Liu, Samuele Bolotta, He Zhu, Yoshua Bengio, Guillaume Dumas:
Attention Schema in Neural Agents. CoRR abs/2305.17375 (2023) - [i33]Rui Hao, Dianbo Liu, Linmei Hu:
Enhancing Human Capabilities through Symbiotic Artificial Intelligence with Shared Sensory Experiences. CoRR abs/2305.19278 (2023) - [i32]Trang Nguyen, Alexander Tong, Kanika Madan, Yoshua Bengio, Dianbo Liu:
Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems. CoRR abs/2310.03579 (2023) - [i31]Zarif Ikram, Ling Pan, Dianbo Liu:
Probabilistic Generative Modeling for Procedural Roundabout Generation for Developing Countries. CoRR abs/2310.03687 (2023) - [i30]Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu:
Physical Reasoning and Object Planning for Household Embodied Agents. CoRR abs/2311.13577 (2023) - [i29]Hang Chen, Yuchuan Jang, Weijie Zhou, Cristian Meo, Ziwei Chen, Dianbo Liu:
Discrete Messages Improve Communication Efficiency among Isolated Intelligent Agents. CoRR abs/2312.15985 (2023) - 2022
- [j5]Dianbo Liu, Kathe P. Fox, Griffin M. Weber, Timothy A. Miller:
Confederated learning in healthcare: Training machine learning models using disconnected data separated by individual, data type and identity for Large-Scale health system Intelligence. J. Biomed. Informatics 134: 104151 (2022) - [j4]Dianbo Liu, Won-Yong Shin, Eli Sprecher, Kathleen Conroy, Omar Santiago, Gal Wachtel, Mauricio Santillana:
Machine learning approaches to predicting no-shows in pediatric medical appointment. npj Digit. Medicine 5 (2022) - [c7]Tianyi Zhang, Shirui Zhang, Ziwei Chen, Yoshua Bengio, Dianbo Liu:
PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records. IEEE Big Data 2022: 4453-4462 - [i28]Dianbo Liu, Alex Lamb, Xu Ji, Pascal Notsawo, Michael Mozer, Yoshua Bengio, Kenji Kawaguchi:
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization. CoRR abs/2202.01334 (2022) - [i27]Mike He Zhu, Léna Néhale Ezzine, Dianbo Liu, Yoshua Bengio:
FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID Data. CoRR abs/2205.09305 (2022) - [i26]Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio:
Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel. CoRR abs/2205.10607 (2022) - [i25]Bonaventure F. P. Dossou, Dianbo Liu, Xu Ji, Moksh Jain, Almer M. van der Sloot, Roger Palou, Michael Tyers, Yoshua Bengio:
Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection. CoRR abs/2209.13518 (2022) - [i24]Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio:
Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. CoRR abs/2210.03022 (2022) - [i23]Dianbo Liu, Moksh Jain, Bonaventure Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio:
GFlowOut: Dropout with Generative Flow Networks. CoRR abs/2210.12928 (2022) - [i22]Dianbo Liu, Karmel W. Choi, Paulo Lizano, William Yuan, Kun-Hsing Yu, Jordan Smoller, Isaac S. Kohane:
Construction of extra-large scale screening tools for risks of severe mental illnesses using real world healthcare data. CoRR abs/2212.10320 (2022) - 2021
- [j3]He Zhu, Dianbo Liu:
FakeSafe: Human Level Steganography Techniques by Disinformation Mapping Using Cycle-Consistent Adversarial Network. IEEE Access 9: 159364-159370 (2021) - [j2]Jianfei Cui, He Zhu, Hao Deng, Ziwei Chen, Dianbo Liu:
FeARH: Federated machine learning with anonymous random hybridization on electronic medical records. J. Biomed. Informatics 117: 103735 (2021) - [c6]Yuwei Cheng, Jiannan Zhu, Mengxin Jiang, Jie Fu, Changsong Pang, Peidong Wang, Kris Sankaran, Olawale Onabola, Yimin Liu, Dianbo Liu, Yoshua Bengio:
FloW: A Dataset and Benchmark for Floating Waste Detection in Inland Waters. ICCV 2021: 10933-10942 - [c5]Olawale Onabola, Zhuang Ma, Yang Xie, Benjamin Akera, Abdulrahman Ibraheem, Jia Xue, Dianbo Liu, Yoshua Bengio:
hBERT + BiasCorp - Fighting Racism on the Web. LT-EDI@EACL 2021: 26-33 - [c4]Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio:
Discrete-Valued Neural Communication. NeurIPS 2021: 2109-2121 - [i21]Olawale Onabola, Zhuang Ma, Yang Xie, Benjamin Akera, Abdulrahman Ibraheem, Jia Xue, Dianbo Liu, Yoshua Bengio:
hBert + BiasCorp - Fighting Racism on the Web. CoRR abs/2104.02242 (2021) - [i20]Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio:
Discrete-Valued Neural Communication. CoRR abs/2107.02367 (2021) - [i19]Tianyi Zhang, Shirui Zhang, Ziwei Chen, Dianbo Liu:
PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records. CoRR abs/2112.05321 (2021) - 2020
- [i18]Jianfei Cui, Dianbo Liu:
Federated machine learning with Anonymous Random Hybridization (FeARH) on medical records. CoRR abs/2001.09751 (2020) - [i17]Dianbo Liu, Timothy A. Miller:
Federated pretraining and fine tuning of BERT using clinical notes from multiple silos. CoRR abs/2002.08562 (2020) - [i16]Dianbo Liu, Leonardo Clemente, Canelle Poirier, Xiyu Ding, Matteo Chinazzi, Jessica T. Davis, Alessandro Vespignani, Mauricio Santillana:
A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models. CoRR abs/2004.04019 (2020) - [i15]Dianbo Liu, He Zhu:
FakeSafe: Human Level Data Protection by Disinformation Mapping using Cycle-consistent Adversarial Network. CoRR abs/2011.11278 (2020) - [i14]Leyu Dai, He Zhu, Dianbo Liu:
Patient similarity: methods and applications. CoRR abs/2012.01976 (2020)
2010 – 2019
- 2019
- [j1]Li Huang, Andrew L. Shea, Huining Qian, Aditya Masurkar, Hao Deng, Dianbo Liu:
Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records. J. Biomed. Informatics 99 (2019) - [c3]Dianbo Liu, Ricky Sahu, Vlad Ignatov, Daniel Gottlieb, Kenneth D. Mandl:
High Performance Computing on Flat FHIR Files Created with the New SMART/HL7 Bulk Data Access Standard. AMIA 2019 - [c2]Dianbo Liu, Dmitriy Dligach, Timothy A. Miller:
Two-stage Federated Phenotyping and Patient Representation Learning. BioNLP@ACL 2019: 283-291 - [i13]Li Huang, Dianbo Liu:
Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records. CoRR abs/1903.09296 (2019) - [i12]Dianbo Liu, Dmitriy Dligach, Timothy A. Miller:
Two-stage Federated Phenotyping and Patient Representation Learning. CoRR abs/1908.05596 (2019) - [i11]Dianbo Liu, Timothy A. Miller, Kenneth D. Mandl:
Confederated Machine Learning on Horizontally and Vertically Separated Medical Data for Large-Scale Health System Intelligence. CoRR abs/1910.02109 (2019) - [i10]Rulin Shao, Hui Liu, Dianbo Liu:
Privacy Preserving Stochastic Channel-Based Federated Learning with Neural Network Pruning. CoRR abs/1910.02115 (2019) - [i9]Rulin Shao, Hongyu He, Hui Liu, Dianbo Liu:
Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving. CoRR abs/1910.11160 (2019) - 2018
- [i8]Shifa Zhang, Anne Kim, Dianbo Liu, Sandeep C. Nuckchadyy, Lauren Huang, Aditya Masurkar, Jingwei Zhang, Lawrence Tseng, Pratheek Karnati, Laura Martínez, Thomas Hardjono, Manolis Kellis, ZhiZhuo Zhang:
Genie: A Secure, Transparent Sharing and Services Platform for Genetic and Health Data. CoRR abs/1811.01431 (2018) - [i7]Dianbo Liu, Timothy A. Miller, Raheel Sayeed, Kenneth D. Mandl:
FADL: Federated-Autonomous Deep Learning for Distributed Electronic Health Record. CoRR abs/1811.11400 (2018) - [i6]Li Huang, Yifeng Yin, Zeng Fu, Shifa Zhang, Hao Deng, Dianbo Liu:
LoAdaBoost: Loss-Based AdaBoost Federated Machine Learning on medical Data. CoRR abs/1811.12629 (2018) - [i5]Zilu Yu, Chen Chen, Dianbo Liu:
Movies Network as the Indicator of Globalization. CoRR abs/1812.09639 (2018) - [i4]Wen Zhou, Dong Zhang, Chen Chen, Dianbo Liu:
Border Effect of Complex Network: An analysis on the cooperation network of movie stars across different regions. CoRR abs/1812.09657 (2018) - [i3]Dianbo Liu, Néstor Sepúlveda, Ming Zheng:
Artificial neural networks condensation: A strategy to facilitate adaption of machine learning in medical settings by reducing computational burden. CoRR abs/1812.09659 (2018) - 2017
- [c1]Dianbo Liu, Fengjiao Peng, Ognjen (Oggi) Rudovic, Rosalind W. Picard:
DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain. AffComp@IJCAI 2017: 1-16 - [i2]Dianbo Liu, Luca Albergante:
Balance of thrones: a network study on 'Game of Thrones'. CoRR abs/1707.05213 (2017) - [i1]Dianbo Liu, Fengjiao Peng, Andrew Shea, Ognjen Rudovic, Rosalind W. Picard:
DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain. CoRR abs/1708.04670 (2017)
Coauthor Index
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last updated on 2024-11-13 23:50 CET by the dblp team
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