Andrew Feng

According to our database, Andrew Feng authored at least 38 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MONAI Label: A framework for AI-assisted interactive labeling of 3D medical images.

Andres Diaz-Pinto, Sachidanand Alle, Vishwesh Nath, Yucheng Tang, Alvin Ihsani, Muhammad Asad, Fernando Pérez-García, Pritesh Mehta, Wenqi Li, Mona Flores, Holger R. Roth, Tom Vercauteren, Daguang Xu, Prerna Dogra, Sébastien Ourselin, Andrew Feng, M. Jorge Cardoso

Medical Image Anal., 2024

C-FedRAG: A Confidential Federated Retrieval-Augmented Generation System.

Parker Addison, Minh-Tuan H. Nguyen, Tomislav Medan, Jinali Shah, Mohammad T. Manzari, Brendan McElrone, Laksh Lalwani, Aboli More, Smita Sharma, Holger R. Roth, Isaac Yang, Chester Chen, Daguang Xu, Yan Cheng, Andrew Feng, Ziyue Xu

CoRR, 2024

Open-Vocabulary High-Resolution 3D (OVHR3D) Data Segmentation and Annotation Framework.

Jiuyi Xu, Meida Chen, Andrew Feng, Zifan Yu, Yangming Shi

CoRR, 2024

Skyeyes: Ground Roaming using Aerial View Images.

Zhiyuan Gao, Wenbin Teng, Gonglin Chen, Jinsen Wu, Ningli Xu, Rongjun Qin, Andrew Feng, Yajie Zhao

CoRR, 2024

Geometry-aware Feature Matching for Large-Scale Structure from Motion.

Gonglin Chen, Jinsen Wu, Haiwei Chen, Wenbin Teng, Zhiyuan Gao, Andrew Feng, Rongjun Qin, Yajie Zhao

CoRR, 2024

Supercharging Federated Learning with Flower and NVIDIA FLARE.

Holger R. Roth, Daniel J. Beutel, Yan Cheng, Javier Fernández-Marqués, Heng Pan, Chester Chen, Zhihong Zhang, Yuhong Wen, Sean Yang, Isaac Yang, Yuan-Ting Hsieh, Ziyue Xu, Daguang Xu, Nicholas D. Lane, Andrew Feng

CoRR, 2024

AtomGS: Atomizing Gaussian Splatting for High-Fidelity Radiance Field.

Rong Liu, Rui Xu, Yue Hu, Meida Chen, Andrew Feng

CoRR, 2024

Empowering Federated Learning for Massive Models with NVIDIA FLARE.

Holger R. Roth, Ziyue Xu, Yuan-Ting Hsieh, Adithya Renduchintala, Isaac Yang, Zhihong Zhang, Yuhong Wen, Sean Yang, Kevin Lu, Kristopher Kersten, Camir Ricketts, Daguang Xu, Chester Chen, Yan Cheng, Andrew Feng

CoRR, 2024

Lazy Resampling: Fast and information preserving preprocessing for deep learning.

Benjamin Murray, Richard Brown, Pengcheng Ma, Eric Kerfoot, Daguang Xu, Andrew Feng, Jorge Cardoso, Sébastien Ourselin, Marc Modat

Comput. Methods Programs Biomed., 2024

Evaluating Vision-Language Models on the TriangleCOPA Benchmark.

Ankur Chemburkar, Andrew S. Gordon, Andrew Feng

Proceedings of the Thirty-Seventh International Florida Artificial Intelligence Research Society Conference, 2024

Combining the Predictions of Out-of-Domain Classifiers Using Etcetera Abduction.

Andrew S. Gordon, Andrew Feng

Proceedings of the 58th Annual Conference on Information Sciences and Systems, 2024

AlignBench: Benchmarking Chinese Alignment of Large Language Models.

Xiao Liu, Xuanyu Lei, Shengyuan Wang, Yue Huang, Andrew Feng, Bosi Wen, Jiale Cheng, Pei Ke, Yifan Xu, Weng Lam Tam, Xiaohan Zhang, Lichao Sun, Xiaotao Gu, Hongning Wang, Jing Zhang, Minlie Huang, Yuxiao Dong, Jie Tang

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation.

Pei Ke, Bosi Wen, Andrew Feng, Xiao Liu, Xuanyu Lei, Jiale Cheng, Shengyuan Wang, Aohan Zeng, Yuxiao Dong, Hongning Wang, Jie Tang, Minlie Huang

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Do Gradient Inversion Attacks Make Federated Learning Unsafe?

Ali Hatamizadeh, Hongxu Yin, Pavlo Molchanov, Andriy Myronenko, Wenqi Li, Prerna Dogra, Andrew Feng, Mona G. Flores, Jan Kautz, Daguang Xu, Holger R. Roth

IEEE Trans. Medical Imaging, 2023

NVIDIA FLARE: Federated Learning from Simulation to Real-World.

Holger R. Roth, Yan Cheng, Yuhong Wen, Isaac Yang, Ziyue Xu, Yuan-Ting Hsieh, Kristopher Kersten, Ahmed Harouni, Can Zhao, Kevin Lu, Zhihong Zhang, Wenqi Li, Andriy Myronenko, Dong Yang, Sean Yang, Nicola Rieke, Abood Quraini, Chester Chen, Daguang Xu, Nic Ma, Prerna Dogra, Mona Flores, Andrew Feng

IEEE Data Eng. Bull., 2023

Generative AI for Medical Imaging: extending the MONAI Framework.

Walter H. L. Pinaya, Mark S. Graham, Eric Kerfoot, Petru-Daniel Tudosiu, Jessica Dafflon, Virginia Fernandez, Pedro Sanchez, Julia Wolleb, Pedro F. Da Costa, Ashay Patel, Hyungjin Chung, Can Zhao, Wei Peng, Zelong Liu, XueYan Mei, Oeslle Lucena, Jong Chul Ye, Sotirios A. Tsaftaris, Prerna Dogra, Andrew Feng, Marc Modat, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

CoRR, 2023

Co-Speech Gesture Synthesis using Discrete Gesture Token Learning.

Shuhong Lu, Youngwoo Yoon, Andrew Feng

IROS, 2023

Discrete Diffusion for Co-Speech Gesture Synthesis.

Ankur Chemburkar, Shuhong Lu, Andrew Feng

Proceedings of the International Conference on Multimodal Interaction, 2023

Searching for the Most Probable Combination of Class Labels Using Etcetera Abduction.

Andrew S. Gordon, Andrew Feng

Proceedings of the 57th Annual Conference on Information Sciences and Systems, 2023

Text-to-Motion Synthesis using Discrete Diffusion Model.

Ankur Chemburkar, Shuhong Lu, Andrew Feng

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022

MONAI: An open-source framework for deep learning in healthcare.

M. Jorge Cardoso, Wenqi Li, Richard Brown, Nic Ma, Eric Kerfoot, Yiheng Wang, Benjamin Murray, Andriy Myronenko, Can Zhao, Dong Yang, Vishwesh Nath, Yufan He, Ziyue Xu, Ali Hatamizadeh, Wentao Zhu, Yun Liu, Mingxin Zheng, Yucheng Tang, Isaac Yang, Michael Zephyr, Behrooz Hashemian, Sachidanand Alle, Mohammad Zalbagi Darestani, Charlie Budd, Marc Modat, Tom Vercauteren, Guotai Wang, Yiwen Li, Yipeng Hu, Yunguan Fu, Benjamin Gorman, Hans J. Johnson, Brad W. Genereaux, Barbaros S. Erdal, Vikash Gupta, Andres Diaz-Pinto, Andre Dourson, Lena Maier-Hein, Paul F. Jaeger, Michael Baumgartner, Jayashree Kalpathy-Cramer, Mona Flores, Justin S. Kirby, Lee A. D. Cooper, Holger R. Roth, Daguang Xu, David Bericat, Ralf Floca, S. Kevin Zhou, Haris Shuaib, Keyvan Farahani, Klaus H. Maier-Hein, Stephen R. Aylward, Prerna Dogra, Sébastien Ourselin, Andrew Feng

CoRR, 2022

MONAI Label: A framework for AI-assisted Interactive Labeling of 3D Medical Images.

Andres Diaz-Pinto, Sachidanand Alle, Alvin Ihsani, Muhammad Asad, Vishwesh Nath, Fernando Pérez-García, Pritesh Mehta, Wenqi Li, Holger R. Roth, Tom Vercauteren, Daguang Xu, Prerna Dogra, Sébastien Ourselin, Andrew Feng, M. Jorge Cardoso

CoRR, 2022

STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset.

Meida Chen, Qingyong Hu, Hugues Thomas, Andrew Feng, Yu Hou, Kyle McCullough, Lucio Soibelman

CoRR, 2022

A Tool for Extracting 3D Avatar-Ready Gesture Animations from Monocular Videos.

Andrew Feng, Samuel Shin, Youngwoo Yoon

Proceedings of the MIG '22: ACM SIGGRAPH Conference on Motion, Interaction and Games, Guanajuato, Mexico, November 3, 2022

DeepEdit: Deep Editable Learning for Interactive Segmentation of 3D Medical Images.

Andres Diaz-Pinto, Pritesh Mehta, Sachidanand Alle, Muhammad Asad, Richard Brown, Vishwesh Nath, Alvin Ihsani, Michela Antonelli, Daniel Palkovics, Csaba Pinter, Ron Alkalay, Steve Pieper, Holger R. Roth, Daguang Xu, Prerna Dogra, Tom Vercauteren, Andrew Feng, Abood Quraini, Sébastien Ourselin, M. Jorge Cardoso

Proceedings of the Data Augmentation, Labelling, and Imperfections, 2022

The DeepMotion entry to the GENEA Challenge 2022.

Shuhong Lu, Andrew Feng

Proceedings of the International Conference on Multimodal Interaction, 2022

STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset.

Meida Chen, Qingyong Hu, Zifan Yu, Hugues Thomas, Andrew Feng, Yu Hou, Kyle McCullough, Fengbo Ren, Lucio Soibelman

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Ground material classification and for UAV-based photogrammetric 3D data A 2D-3D Hybrid Approach.

Meida Chen, Andrew Feng, Yu Hou, Kyle McCullough, Pratusha Bhuvana Prasad, Lucio Soibelman

CoRR, 2021

2020

3D Photogrammetry Point Cloud Segmentation Using a Model Ensembling Framework.

Meida Chen, Andrew Feng, Kyle McCullough, Pratusha Bhuvana Prasad, Ryan McAlinden, Lucio Soibelman

J. Comput. Civ. Eng., 2020

Utilizing Satellite Imagery Datasets and Machine Learning Data Models to Evaluate Infrastructure Change in Undeveloped Regions.

Kyle McCullough, Andrew Feng, Meida Chen, Ryan McAlinden

CoRR, 2020

Semantic Segmentation and Data Fusion of Microsoft Bing 3D Cities and Small UAV-based Photogrammetric Data.

Meida Chen, Andrew Feng, Kyle McCullough, Pratusha Bhuvana Prasad, Ryan McAlinden, Lucio Soibelman

CoRR, 2020

Generating synthetic photogrammetric data for training deep learning based 3D point cloud segmentation models.

Meida Chen, Andrew Feng, Kyle McCullough, Pratusha Bhuvana Prasad, Ryan McAlinden, Lucio Soibelman

CoRR, 2020

Fully Automated Photogrammetric Data Segmentation and Object Information Extraction Approach for Creating Simulation Terrain.

Meida Chen, Andrew Feng, Kyle McCullough, Pratusha Bhuvana Prasad, Ryan McAlinden, Lucio Soibelman, Mike Enloe

CoRR, 2020

Recognizing Multiplayer Behaviors Using Synthetic Training Data.

Andrew Feng, Andrew S. Gordon

Proceedings of the IEEE Conference on Games, 2020

2019

Privacy-Preserving Federated Brain Tumour Segmentation.

Wenqi Li, Fausto Milletarì, Daguang Xu, Nicola Rieke, Jonny Hancox, Wentao Zhu, Maximilian Baust, Yan Cheng, Sébastien Ourselin, M. Jorge Cardoso, Andrew Feng

Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

Latent Terrain Representations for Trajectory Prediction.

Andrew Feng, Andrew S. Gordon

Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data, 2019

2016

Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising.

Mihajlo Grbovic, Nemanja Djuric, Vladan Radosavljevic, Fabrizio Silvestri, Ricardo Baeza-Yates, Andrew Feng, Erik Ordentlich, Lee Yang, Gavin Owens

Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016

Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale.

Firas Abuzaid, Joseph K. Bradley, Feynman T. Liang, Andrew Feng, Lee Yang, Matei Zaharia, Ameet Talwalkar

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016