Dianbo Liu - RankMe

105 papers A* 10B 1Misc 1Journal 89Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AI-generated data contamination erodes pathological variability and diagnostic reliability. CoRR Hongyu He, Shaowen Xiang, Ye Zhang, Yingtao Zhu, Jin Zhang, Hao Deng, Emily Alsentzer, Yun Liu, Qingyu Chen, Kun-Hsing Yu, Andrew Marshall, Tingting Chen, Srinivas Anumasa, Daniel Ebner, Dean Ho, Kee Yuan Ngiam, Ching-Yu Cheng, Dianbo Liu
2026	A*	`conf`	BayesAgent: Bayesian Agentic Reasoning Under Uncertainty via Verbalized Probabilistic Graphical Modeling. AAAI Hengguan Huang, Xing Shen, Guang-Yuan Hao, Songtao Wang, Lingfa Meng, Dianbo Liu, David A. Duchêne, Hao Wang, Samir Bhatt
2026	J	`jnl`	Bridging Mechanistic Interpretability and Prompt Engineering with Gradient Ascent for Interpretable Persona Control. CoRR Harshvardhan Saini, Yiming Tang, Dianbo Liu
2026	J	`jnl`	Early Quantization Shrinks Codebook: A Simple Fix for Diversity-Preserving Tokenization. CoRR Wenhao Zhao, Qiran Zou, Rushi Shah, Yudi Wu, Zhouhan Lin, Dianbo Liu
2026	J	`jnl`	Expected Return Causes Outcome-Level Mode Collapse in Reinforcement Learning and How to Fix It with Inverse Probability Scaling. CoRR Abhijeet Sinha, Sundari Elango, Dianbo Liu
2026	J	`jnl`	Mitigating Premature Discretization with Progressive Quantization for Robust Vector Tokenization. CoRR Wenhao Zhao, Qiran Zou, Zhouhan Lin, Dianbo Liu
2026	J	`jnl`	Navigating heterogeneous protein landscapes through geometry-aware smoothing. CoRR Srinivas Anumasa, Barath Chandran. C, Tingting Chen, Nuwaisir Mohammad Rahman, Yingtao Zhu, Rushi Shah, Hongyu He, Peisong Zhang, Yizhen Liao, Yiming Tang, Yong Shen, Tianfan Fu, Rui Qing, Xiao Li, Sebastian Maurer-Stroh, Xinyi Su, ZhiZhuo Zhang, Dianbo Liu
2026	J	`jnl`	VQKV: High-Fidelity and High-Ratio Cache Compression via Vector-Quantization. CoRR Yixuan Wang, Qingyu Shi, Jiayu Zhou, Dianbo Liu, Ziwei He, Zhouhan Lin
2025	J	`jnl`	A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers. CoRR Meng Wang, Tian Lin, Qingshan Hou, Aidi Lin, Jingcheng Wang, Qingsheng Peng, Truong X. Nguyen, Danqi Fang, Ke Zou, Ting Xu, Cancan Xue, Ten Cheer Quek, Qinkai Yu, Minxin Liu, Hui Zhou, Zixuan Xiao, Guiqin He, Huiyu Liang, Tingkun Shi, Man Chen, Linna Liu, Yuanyuan Peng, Lianyu Wang, Qiuming Hu, Junhong Chen, Zhenhua Zhang, Cheng Chen, Yitian Zhao, Dianbo Liu, Jianhua Wu, Xinjian Chen, Changqing Zhang, Triet Thanh Nguyen, Yanda Meng, Yalin Zheng, Yih Chung Tham, Carol Y. Cheung, Huazhu Fu, Haoyu Chen, Ching-Yu Cheng
2025	J	`jnl`	Attention Schema-based Attention Control (ASAC): A Cognitive-Inspired Approach for Attention Management in Transformers. CoRR Krati Saxena, Federico Jurado Ruiz, Guido Manzi, Dianbo Liu, Alex Lamb
2025	J	`jnl`	Auto-Bench: An Automated Benchmark for Scientific Discovery in LLMs. CoRR Tingting Chen, Srinivas Anumasa, Beibei Lin, Vedant Shah, Anirudh Goyal, Dianbo Liu
2025	J	`jnl`	BEnchmarking LLMs for Ophthalmology (BELO) for Ophthalmological Knowledge and Reasoning. CoRR Sahana Srinivasan, Xuguang Ai, Thaddaeus Wai Soon Lo, Aidan Gilson, Minjie Zou, Ke Zou, Hyunjae Kim, Mingjia Yang, Krithi Pushpanathan, Samantha Min Er Yew, Wan Ting Loke, Jocelyn Hui Lin Goh, Yibing Chen, Yiming Kong, Emily Yuelei Fu, Michelle Ongyong Hui, Kristen Nwanyanwu, Amisha D. Dave, Kelvin Zhenghao Li, Chen-Hsin Sun, Mark A. Chia, Gabriel Dawei Yang, Wendy Meihua Wong, David Ziyou Chen, Dianbo Liu, Maxwell B. Singer, Fares Antaki, Luciano V. Del Priore, Jost B. Jonas, Ron A. Adelman, Qingyu Chen, Yih-Chung Tham
2025	J	`jnl`	Benchmarking Next-Generation Reasoning-Focused Large Language Models in Ophthalmology: A Head-to-Head Evaluation on 5,888 Items. CoRR Minjie Zou, Sahana Srinivasan, Thaddaeus Wai Soon Lo, Ke Zou, Gabriel Dawei Yang, Xuguang Ai, Hyunjae Kim, Maxwell B. Singer, Fares Antaki, Kelvin Li, Robert Chang, Marcus Tan, David Ziyou Chen, Dianbo Liu, Qingyu Chen, Yih Chung Tham
2025	J	`jnl`	CXR-LanIC: Language-Grounded Interpretable Classifier for Chest X-Ray Diagnosis. CoRR Yiming Tang, Wenjia Zhong, Rushi Shah, Dianbo Liu
2025	J	`jnl`	Can OpenAI o1 Reason Well in Ophthalmology? A 6,990-Question Head-to-Head Evaluation Study. CoRR Sahana Srinivasan, Xuguang Ai, Minjie Zou, Ke Zou, Hyunjae Kim, Thaddaeus Wai Soon Lo, Krithi Pushpanathan, Yiming Kong, Anran Li, Maxwell B. Singer, Kai Jin, Fares Antaki, Ziyou Chen, Dianbo Liu, Ron A. Adelman, Qingyu Chen, Yih Chung Tham
2025	J	`jnl`	Data-Dependent Smoothing for Protein Discovery with Walk-Jump Sampling. CoRR Srinivas Anumasa, Barath Chandran. C, Tingting Chen, Dianbo Liu
2025	J	`jnl`	Deconstructing Generative Diversity: An Information Bottleneck Analysis of Discrete Latent Generative Models. CoRR Yudi Wu, Wenhao Zhao, Dianbo Liu
2025	J	`jnl`	Evolution guided generative flow networks. Trans. Mach. Learn. Res. Zarif Ikram, Ling Pan, Dianbo Liu
2025	J	`jnl`	Explore-Execute Chain: Towards an Efficient Structured Reasoning Paradigm. CoRR Kaisen Yang, Lixuan He, Rushi Shah, Kaicheng Yang, Qinwei Ma, Dianbo Liu, Alex Lamb
2025	J	`jnl`	FML-bench: A Benchmark for Automatic ML Research Agents Highlighting the Importance of Exploration Breadth. CoRR Qiran Zou, Hein-Mun Lam, Wenhao Zhao, Yiming Tang, Tingting Chen, Samson Yu, Tianyi Zhang, Chang Liu, Xiangyang Ji, Dianbo Liu
2025	J	`jnl`	FedWeight: mitigating covariate shift of federated learning on electronic health records data through patients re-weighting. npj Digit. Medicine He Zhu, Jun Bai, Na Li, Xiaoxiao Li, Dianbo Liu, David L. Buckeridge, Yue Li
2025	A*	`conf`	Flow Factorization for Efficient Generative Flow Networks. AAAI Jiashun Liu, Chunhui Li, Cheng-Hao Liu, Dianbo Liu, Qingpeng Cai, Ling Pan
2025	J	`jnl`	How does My Model Fail? Automatic Identification and Interpretation of Physical Plausibility Failure Modes with Matryoshka Transcoders. CoRR Yiming Tang, Abhijeet Sinha, Dianbo Liu
2025	J	`jnl`	HypoSpace: Evaluating LLM Creativity as Set-Valued Hypothesis Generators under Underdetermination. CoRR Tingting Chen, Beibei Lin, Zifeng Yuan, Qiran Zou, Hongyu He, Yew-Soon Ong, Anirudh Goyal, Dianbo Liu
2025	J	`jnl`	Interpretable Evaluation of AI-Generated Content with Language-Grounded Sparse Encoders. CoRR Yiming Tang, Arash Lagzian, Srinivas Anumasa, Qiran Zou, Trang Nguyen, Ehsan Adeli, Ching-Yu Cheng, Yilun Du, Dianbo Liu
2025	J	`jnl`	JEDI: Latent End-to-end Diffusion Mitigates Agent-Human Performance Asymmetry in Model-Based Reinforcement Learning. CoRR Jing Yu Lim, Zarif Ikram, Samson Yu, Haozhe Ma, Tze-Yun Leong, Dianbo Liu
2025	J	`jnl`	Laplacian Score Sharpening for Mitigating Hallucination in Diffusion Models. CoRR Barath Chandran. C, Srinivas Anumasa, Dianbo Liu
2025	J	`jnl`	Multi-Novelty: Improve the Diversity and Novelty of Contents Generated by Large Language Models via inference-time Multi-Views Brainstorming. CoRR Arash Lagzian, Srinivas Anumasa, Dianbo Liu
2025	J	`jnl`	On the Theoretical Foundation of Sparse Dictionary Learning in Mechanistic Interpretability. CoRR Yiming Tang, Harshvardhan Saini, Yizhen Liao, Dianbo Liu
2025	J	`jnl`	Toward a Unified Benchmark and Taxonomy of Stochastic Environments. CoRR Aryan Amit Barsainyan, Jing Yu Lim, Dianbo Liu
2025	—	`conf`	Uncertainty-Aware Multimodal Fusion for Reliable Fundus Disease Classification Using a Vision-Language Foundation Model. OMIA@MICCAI Meng Wang, Tian Lin, Aidi Lin, Ke Zou, Ting Xu, Yanda Meng, Dianbo Liu, Yih Chung Tham, Haoyu Chen, Huazhu Fu
2025	A*	`conf`	Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos. ICML Tianyi Zhang, Yu Cao, Dianbo Liu
2024	J	`jnl`	Balance of Number of Embedding and their Dimensions in Vector Quantization. CoRR Hang Chen, Sankepally Sainath Reddy, Ziwei Chen, Dianbo Liu
2024	J	`jnl`	BarlowTwins-CXR : Enhancing Chest X-Ray abnormality localization in heterogeneous data with cross-domain self-supervised learning. CoRR Haoyue Sheng, Linrui Ma, Jean-Francois Samson, Dianbo Liu
2024	J	`jnl`	BarlowTwins-CXR: enhancing chest X-ray abnormality localization in heterogeneous data with cross-domain self-supervised learning. BMC Medical Informatics Decis. Mak. Haoyue Sheng, Linrui Ma, Jean-Francois Samson, Dianbo Liu
2024	J	`jnl`	Bifurcated Generative Flow Networks. CoRR Chunhui Li, Cheng-Hao Liu, Dianbo Liu, Qingpeng Cai, Ling Pan
2024	J	`jnl`	Brain-inspired continual pre-trained learner via silent synaptic consolidation. CoRR Xuming Ran, Juntao Yao, Yusong Wang, Mingkun Xu, Dianbo Liu
2024	J	`jnl`	CodeUnlearn: Amortized Zero-Shot Machine Unlearning in Language Models Using Discrete Concept. CoRR Yuxuan Wu, Bonaventure F. P. Dossou, Dianbo Liu
2024	J	`jnl`	Common and Rare Fundus Diseases Identification Using Vision-Language Foundation Model with Knowledge of Over 400 Diseases. CoRR 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
2024	J	`jnl`	Evolution Guided Generative Flow Networks. CoRR Zarif Ikram, Ling Pan, Dianbo Liu
2024	J	`jnl`	Gaussian Mixture Vector Quantization with Aggregated Categorical Posterior. CoRR Mingyuan Yan, Jiawei Wu, Rushi Shah, Dianbo Liu
2024	J	`jnl`	Gradient-guided discrete walk-jump sampling for biological sequence generation. Trans. Mach. Learn. Res. Zarif Ikram, Dianbo Liu, M. Saifur Rahman
2024	J	`jnl`	Improve Robustness of Eye Disease Detection by including Learnable Probabilistic Discrete Latent Variables into Machine Learning Models. CoRR Anirudh Prabhakaran, YeKun Xiao, Ching-Yu Cheng, Dianbo Liu
2024	J	`jnl`	Improving Discrete Optimisation Via Decoupled Straight-Through Gumbel-Softmax. CoRR Rushi Shah, Mingyuan Yan, Michael Curtis Mozer, Dianbo Liu
2024	J	`jnl`	Language Enhanced Model for Eye (LEME): An Open-Source Ophthalmology-Specific Large Language Model. CoRR 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
2024	J	`jnl`	Masked Generative Priors Improve World Models Sequence Modelling Capabilities. CoRR Cristian Meo, Mircea Lica, Zarif Ikram, Akihiro Nakano, Vedant Shah, Aniket Rajiv Didolkar, Dianbo Liu, Anirudh Goyal, Justin Dauwels
2024	J	`jnl`	Physical Reasoning and Object Planning for Household Embodied Agents. Trans. Mach. Learn. Res. Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu
2024	J	`jnl`	Representation Collapsing Problems in Vector Quantization. CoRR Wenhao Zhao, Qiran Zou, Rushi Shah, Dianbo Liu
2024	J	`jnl`	Safety challenges of AI in medicine. CoRR 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
2024	J	`jnl`	Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos. CoRR Tianyi Zhang, Yu Cao, Dianbo Liu
2024	A*	`conf`	Unsupervised Concept Discovery Mitigates Spurious Correlations. ICML Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi
2024	J	`jnl`	Unsupervised Concept Discovery Mitigates Spurious Correlations. CoRR Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi
2024	J	`jnl`	VQSynery: Robust Drug Synergy Prediction With Vector Quantization Mechanism. CoRR Jiawei Wu, Mingyuan Yan, Dianbo Liu
2024	J	`jnl`	Verbalized Probabilistic Graphical Modeling with Large Language Models. CoRR Hengguan Huang, Xing Shen, Songtao Wang, Dianbo Liu, Hao Wang
2023	A*	`conf`	Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness. AAAI Dianbo Liu, Alex Lamb, Xu Ji, Pascal Tikeng Notsawo Jr., Michael Mozer, Yoshua Bengio, Kenji Kawaguchi
2023	J	`jnl`	Attention Schema in Neural Agents. CoRR Dianbo Liu, Samuele Bolotta, He Zhu, Yoshua Bengio, Guillaume Dumas
2023	J	`jnl`	Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems. CoRR Bailey Trang Nguyen, Alexander Tong, Kanika Madan, Yoshua Bengio, Dianbo Liu
2023	J	`jnl`	Discrete Messages Improve Communication Efficiency among Isolated Intelligent Agents. CoRR Hang Chen, Yuchuan Jang, Weijie Zhou, Cristian Meo, Ziwei Chen, Dianbo Liu
2023	J	`jnl`	Enhancing Human Capabilities through Symbiotic Artificial Intelligence with Shared Sensory Experiences. CoRR Rui Hao, Dianbo Liu, Linmei Hu
2023	A*	`conf`	GFlowOut: Dropout with Generative Flow Networks. ICML 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
2023	J	`jnl`	Physical Reasoning and Object Planning for Household Embodied Agents. CoRR Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu
2023	J	`jnl`	Probabilistic Generative Modeling for Procedural Roundabout Generation for Developing Countries. CoRR Zarif Ikram, Ling Pan, Dianbo Liu
2023	A*	`conf`	Reusable Slotwise Mechanisms. NeurIPS Bailey Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio
2023	J	`jnl`	Reusable Slotwise Mechanisms. CoRR Bailey Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio
2023	A*	`conf`	Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. ICLR Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Curtis Mozer, Nicolas Heess, Yoshua Bengio
2022	J	`jnl`	Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization. CoRR Dianbo Liu, Alex Lamb, Xu Ji, Pascal Notsawo, Michael Mozer, Yoshua Bengio, Kenji Kawaguchi
2022	J	`jnl`	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 Dianbo Liu, Kathe P. Fox, Griffin M. Weber, Tim Miller
2022	J	`jnl`	Construction of extra-large scale screening tools for risks of severe mental illnesses using real world healthcare data. CoRR Dianbo Liu, Karmel W. Choi, Paulo Lizano, William Yuan, Kun-Hsing Yu, Jordan Smoller, Isaac S. Kohane
2022	J	`jnl`	Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel. CoRR Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio
2022	J	`jnl`	FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID Data. CoRR Mike He Zhu, Léna Néhale Ezzine, Dianbo Liu, Yoshua Bengio
2022	J	`jnl`	GFlowOut: Dropout with Generative Flow Networks. CoRR 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
2022	J	`jnl`	Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection. CoRR Bonaventure F. P. Dossou, Dianbo Liu, Xu Ji, Moksh Jain, Almer M. van der Sloot, Roger Palou, Michael Tyers, Yoshua Bengio
2022	J	`jnl`	Machine learning approaches to predicting no-shows in pediatric medical appointment. npj Digit. Medicine Dianbo Liu, Won-Yong Shin, Eli Sprecher, Kathleen Conroy, Omar Santiago, Gal Wachtel, Mauricio Santillana
2022	B	`conf`	PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records. IEEE Big Data Tianyi Zhang, Shirui Zhang, Ziwei Chen, Yoshua Bengio, Dianbo Liu
2022	J	`jnl`	Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. CoRR Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio
2021	A*	`conf`	Discrete-Valued Neural Communication. NeurIPS Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio
2021	J	`jnl`	Discrete-Valued Neural Communication. CoRR Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio
2021	J	`jnl`	FakeSafe: Human Level Steganography Techniques by Disinformation Mapping Using Cycle-Consistent Adversarial Network. IEEE Access He Zhu, Dianbo Liu
2021	J	`jnl`	FeARH: Federated machine learning with anonymous random hybridization on electronic medical records. J. Biomed. Informatics Jianfei Cui, He Zhu, Hao Deng, Ziwei Chen, Dianbo Liu
2021	A*	`conf`	FloW: A Dataset and Benchmark for Floating Waste Detection in Inland Waters. ICCV Yuwei Cheng, Jiannan Zhu, Mengxin Jiang, Jie Fu, Changsong Pang, Peidong Wang, Kris Sankaran, Olawale Onabola, Yimin Liu, Dianbo Liu, Yoshua Bengio
2021	J	`jnl`	PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records. CoRR Tianyi Zhang, Shirui Zhang, Ziwei Chen, Dianbo Liu
2021	—	`conf`	hBERT + BiasCorp - Fighting Racism on the Web. LT-EDI@EACL Olawale Onabola, Zhuang Ma, Yang Xie, Benjamin Akera, Abdulrahman Ibraheem, Jia Xue, Dianbo Liu, Yoshua Bengio
2021	J	`jnl`	hBert + BiasCorp - Fighting Racism on the Web. CoRR Olawale Onabola, Zhuang Ma, Yang Xie, Benjamin Akera, Abdulrahman Ibraheem, Jia Xue, Dianbo Liu, Yoshua Bengio
2020	J	`jnl`	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 Dianbo Liu, Leonardo Clemente, Canelle Poirier, Xiyu Ding, Matteo Chinazzi, Jessica T. Davis, Alessandro Vespignani, Mauricio Santillana
2020	J	`jnl`	FakeSafe: Human Level Data Protection by Disinformation Mapping using Cycle-consistent Adversarial Network. CoRR Dianbo Liu, He Zhu
2020	J	`jnl`	Federated machine learning with Anonymous Random Hybridization (FeARH) on medical records. CoRR Jianfei Cui, Dianbo Liu
2020	J	`jnl`	Federated pretraining and fine tuning of BERT using clinical notes from multiple silos. CoRR Dianbo Liu, Tim Miller
2020	J	`jnl`	Patient similarity: methods and applications. CoRR Leyu Dai, He Zhu, Dianbo Liu
2019	J	`jnl`	Confederated Machine Learning on Horizontally and Vertically Separated Medical Data for Large-Scale Health System Intelligence. CoRR Dianbo Liu, Tim Miller, Kenneth D. Mandl
2019	Misc	`conf`	High Performance Computing on Flat FHIR Files Created with the New SMART/HL7 Bulk Data Access Standard. AMIA Dianbo Liu, Ricky Sahu, Vlad Ignatov, Daniel Gottlieb, Kenneth D. Mandl
2019	J	`jnl`	Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records. CoRR Li Huang, Dianbo Liu
2019	J	`jnl`	Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records. J. Biomed. Informatics Li Huang, Andrew L. Shea, Huining Qian, Aditya Masurkar, Hao Deng, Dianbo Liu
2019	J	`jnl`	Privacy Preserving Stochastic Channel-Based Federated Learning with Neural Network Pruning. CoRR Rulin Shao, Hui Liu, Dianbo Liu
2019	J	`jnl`	Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving. CoRR Rulin Shao, Hongyu He, Hui Liu, Dianbo Liu
2019	—	`conf`	Two-stage Federated Phenotyping and Patient Representation Learning. BioNLP@ACL Dianbo Liu, Dmitriy Dligach, Timothy Miller
2019	J	`jnl`	Two-stage Federated Phenotyping and Patient Representation Learning. CoRR Dianbo Liu, Dmitriy Dligach, Timothy Miller
2018	J	`jnl`	Artificial neural networks condensation: A strategy to facilitate adaption of machine learning in medical settings by reducing computational burden. CoRR Dianbo Liu, Néstor Sepúlveda, Ming Zheng
2018	J	`jnl`	Border Effect of Complex Network: An analysis on the cooperation network of movie stars across different regions. CoRR Wen Zhou, Dong Zhang, Chen Chen, Dianbo Liu
2018	J	`jnl`	FADL: Federated-Autonomous Deep Learning for Distributed Electronic Health Record. CoRR Dianbo Liu, Timothy Miller, Raheel Sayeed, Kenneth D. Mandl
2018	J	`jnl`	Genie: A Secure, Transparent Sharing and Services Platform for Genetic and Health Data. CoRR 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
2018	J	`jnl`	LoAdaBoost: Loss-Based AdaBoost Federated Machine Learning on medical Data. CoRR Li Huang, Yifeng Yin, Zeng Fu, Shifa Zhang, Hao Deng, Dianbo Liu
2018	J	`jnl`	Movies Network as the Indicator of Globalization. CoRR Zilu Yu, Chen Chen, Dianbo Liu
2017	J	`jnl`	Balance of thrones: a network study on 'Game of Thrones'. CoRR Dianbo Liu, Luca Albergante
2017	—	`conf`	DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain. AffComp@IJCAI Dianbo Liu, Fengjiao Peng, Ognjen (Oggi) Rudovic, Rosalind W. Picard
2017	J	`jnl`	DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain. CoRR Dianbo Liu, Fengjiao Peng, Andrew Shea, Ognjen Rudovic, Rosalind W. Picard