Praneeth Vepakomma

Praneeth Vepakomma

Massachusetts Institute of Technology, MBZUAI
在 mit.edu 的电子邮件经过验证
被引用次数：8199
Trustworthy ML Responsible AI Distributed ML Distributed Statistical Inference Privacy
Amir Houmansadr

Amir Houmansadr

University of Massachusetts Amherst
在 cs.umass.edu 的电子邮件经过验证
被引用次数：7069
Privacy-enhancing technologies Trustworthy ML Network traffic analysis
Lukas Ruff

Lukas Ruff

Aignostics
在 aignostics.com 的电子邮件经过验证
被引用次数：4674
Machine Learning Deep Learning Trustworthy ML Anomaly Detection Digital Pathology
Payel Das

Payel Das

Manager and Principal Research Staff Member, AI research, IBM Watson, NY
在 us.ibm.com 的电子邮件经过验证
被引用次数：4437
trustworthy ML generative AI bio-inspired AI AI4Science statistical physics
Sara Hooker

Sara Hooker

Head of Cohere For AI
在 cohere.com 的电子邮件经过验证
被引用次数：4115
Machine learning efficiency robustness interpretability trustworthy ML
Jian Liang (梁坚)

Jian Liang (梁坚)

NLPR, Institute of Automation, Chinese Academy of Sciences
在 nlpr.ia.ac.cn 的电子邮件经过验证
被引用次数：3826
Trustworthy ML Representation Learning Domain Adaptation Federated Learning AI Safety
Chaochao Chen

Chaochao Chen

Zhejiang University
在 zju.edu.cn 的电子邮件经过验证
被引用次数：3610
Trustworthy ML Privacy-Preserving ML Federated Learning Recommender Systems
Elan Rosenfeld

Elan Rosenfeld

PhD Student, Carnegie Mellon University
在 andrew.cmu.edu 的电子邮件经过验证
被引用次数：2638
machine learning robustness trustworthy ML representation learning
Hadi Salman

Hadi Salman

OpenAI, MIT
在 mit.edu 的电子邮件经过验证
被引用次数：2518
Deep Learning Robustness Trustworthy ML LLMs
Zhengzhong Tu

Zhengzhong Tu

Texas A&M University, Google Research, University of Texas at Austin
在 tamu.edu 的电子邮件经过验证
被引用次数：2005
Multimodal AI Generative AI Autonomous Driving Trustworthy ML MLSys
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