Dianbo Liu

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 63

Top Topics

Privacy Preserving

Machine Learning

Vector Quantization

Medical Records

Top Venues

J. Biomed. Informatics

Publications

Hang Chen, Sankepally Sainath Reddy, Ziwei Chen, Dianbo Liu
Balance of Number of Embedding and their Dimensions in Vector Quantization. CoRR (2024)
Jiawei Wu, Mingyuan Yan, Dianbo Liu
VQSynery: Robust Drug Synergy Prediction With Vector Quantization Mechanism. CoRR (2024)
Zarif Ikram, Ling Pan, Dianbo Liu
Evolution Guided Generative Flow Networks. CoRR (2024)
Tianyi Zhang, Yu Cao, Dianbo Liu
Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos. CoRR (2024)
Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu
Physical Reasoning and Object Planning for Household Embodied Agents. Trans. Mach. Learn. Res. 2024 (2024)
Hengguan Huang, Xing Shen, Songtao Wang, Dianbo Liu, Hao Wang
Verbalized Probabilistic Graphical Modeling with Large Language Models. CoRR (2024)
Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi
Unsupervised Concept Discovery Mitigates Spurious Correlations. CoRR (2024)
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 (2024)
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 (2024)
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 (2024)
Chunhui Li, Cheng-Hao Liu, Dianbo Liu, Qingpeng Cai, Ling Pan
Bifurcated Generative Flow Networks. CoRR (2024)
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) (2024)
Dianbo Liu, Samuele Bolotta, He Zhu, Yoshua Bengio, Guillaume Dumas
Attention Schema in Neural Agents. CoRR (2023)
Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio
Reusable Slotwise Mechanisms. CoRR (2023)
Trang Nguyen, Alexander Tong, Kanika Madan, Yoshua Bengio, Dianbo Liu
Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems. CoRR (2023)
Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu
Physical Reasoning and Object Planning for Household Embodied Agents. CoRR (2023)
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)
Rui Hao, Dianbo Liu, Linmei Hu
Enhancing Human Capabilities through Symbiotic Artificial Intelligence with Shared Sensory Experiences. CoRR (2023)
Hang Chen, Yuchuan Jang, Weijie Zhou, Cristian Meo, Ziwei Chen, Dianbo Liu
Discrete Messages Improve Communication Efficiency among Isolated Intelligent Agents. CoRR (2023)
Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio
Reusable Slotwise Mechanisms. NeurIPS (2023)
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)
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)
Zarif Ikram, Ling Pan, Dianbo Liu
Probabilistic Generative Modeling for Procedural Roundabout Generation for Developing Countries. CoRR (2023)
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)
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 (2022)
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 (2022)
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 (2022)
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 (2022)
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 (2022)
Dianbo Liu, Alex Lamb, Xu Ji, Pascal Notsawo, Michael Mozer, Yoshua Bengio, Kenji Kawaguchi
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization. CoRR (2022)
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 (2022)
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. Big Data (2022)
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 (2022)
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 (2021)
Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio
Discrete-Valued Neural Communication. CoRR (2021)
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)
Olawale Onabola, Zhuang Ma, Yang Xie, Benjamin Akera, Abdulrahman Ibraheem, Jia Xue, Dianbo Liu, Yoshua Bengio
hBert + BiasCorp - Fighting Racism on the Web. CoRR (2021)
He Zhu, Dianbo Liu
FakeSafe: Human Level Steganography Techniques by Disinformation Mapping Using Cycle-Consistent Adversarial Network. IEEE Access 9 (2021)
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 (2021)
Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio
Discrete-Valued Neural Communication. NeurIPS (2021)
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)
Dianbo Liu, Timothy A. Miller
Federated pretraining and fine tuning of BERT using clinical notes from multiple silos. CoRR (2020)
Jianfei Cui, Dianbo Liu
Federated machine learning with Anonymous Random Hybridization (FeARH) on medical records. CoRR (2020)
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 (2020)
Dianbo Liu, He Zhu
FakeSafe: Human Level Data Protection by Disinformation Mapping using Cycle-consistent Adversarial Network. CoRR (2020)
Leyu Dai, He Zhu, Dianbo Liu
Patient similarity: methods and applications. CoRR (2020)
Rulin Shao, Hongyu He, Hui Liu, Dianbo Liu
Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving. CoRR (2019)
Dianbo Liu, Dmitriy Dligach, Timothy A. Miller
Two-stage Federated Phenotyping and Patient Representation Learning. CoRR (2019)
Rulin Shao, Hui Liu, Dianbo Liu
Privacy Preserving Stochastic Channel-Based Federated Learning with Neural Network Pruning. CoRR (2019)
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)
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 (2019)
Dianbo Liu, Dmitriy Dligach, Timothy A. Miller
Two-stage Federated Phenotyping and Patient Representation Learning. BioNLP@ACL (2019)
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)
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 (2019)
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 (2018)
Dianbo Liu, Timothy A. Miller, Raheel Sayeed, Kenneth D. Mandl
FADL: Federated-Autonomous Deep Learning for Distributed Electronic Health Record. CoRR (2018)
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 (2018)
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 (2018)
Zilu Yu, Chen Chen, Dianbo Liu
Movies Network as the Indicator of Globalization. CoRR (2018)
Li Huang, Yifeng Yin, Zeng Fu, Shifa Zhang, Hao Deng, Dianbo Liu
LoAdaBoost: Loss-Based AdaBoost Federated Machine Learning on medical Data. CoRR (2018)
Dianbo Liu, Luca Albergante
Balance of thrones: a network study on 'Game of Thrones'. CoRR (2017)
Dianbo Liu, Fengjiao Peng, Ognjen (Oggi) Rudovic, Rosalind W. Picard
DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain. AffComp@IJCAI (2017)
Dianbo Liu, Fengjiao Peng, Andrew Shea, Ognjen Rudovic, Rosalind W. Picard
DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain. CoRR (2017)