Research

Cleanlab research featured in the News

Additional publications by our team

• Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

  Anish Athalye, Nicholas Carlini, and David Wagner

  35th International Conference on Machine Learning (ICML), 2018

  Best Paper Award, Code

• EgoCom: A Multi-person Multi-modal Egocentric Communications Dataset

  Curtis Northcutt, Zha Shengxin, Steven Lovegrove, and Richard Newcombe

  IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020

  Code

• Time-Varying Propensity Score to Bridge the Gap between the Past and Present

  Rasool Fakoor, Jonas Mueller, Zachary Lipton, Pratik Chaudhari, and Alex Smola

  International Conference on Learning Representations (ICLR), 2024

• Adaptive Interest for Emphatic Reinforcement Learning

  Martin Klissarov, Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Taesup Kim, and Alex Smola

  Advances in Neural Information Processing Systems (NeurIPS), 2022

• Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features

  Jiuhai Chen, Jonas Mueller, Vassilis Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, and David Wipf

  International Conference on Learning Representations (ICLR), 2022

• Deep learning for the partially linear Cox model

  Qixian Zhong, Jonas Mueller, and Jane-Ling Wang

  Annals of Statistics, 2022

• Flexible Model Aggregation for Quantile Regression

  Rasool Fakoor, Taesup Kim, Jonas Mueller, Alexander Smola, and Ryan Tibshirani

  Journal of Machine Learning Research, 2023

• Benchmarking Multimodal AutoML for Tabular Data with Text Fields

  Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, and Alex Smola

  35th Conference on Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks, 2021

  Code

• Overinterpretation reveals image classification model pathologies

  Brandon Carter, Siddhartha Jain, Jonas Mueller, and David Gifford

  Advances in Neural Information Processing Systems (NeurIPS), 2021

  Code

• Deep Extended Hazard Models for Survival Analysis

  Qixian Zhong, Jonas Mueller, and Jane-Ling Wang

  Advances in Neural Information Processing Systems (NeurIPS), 2021

• Continuous Doubly Constrained Batch Reinforcement Learning

  Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Pratik Chaudhari, and Alex Smola

  Advances in Neural Information Processing Systems (NeurIPS), 2021

  Code

• Graph Neural Networks Formed via Layer-wise Ensembles of Heterogeneous Base Models

  Jiuhai Chen, Jonas Mueller, Vassilis Ioannidis, Tom Goldstein, and David Wipf

  Transactions on Machine Learning Research (TMLR), 2024

• Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges

  Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, and Rasool Fakoor

  Conference on Lifelong Learning Agents (CoLLAs), 2023

• Verifying Hardware Security Modules with Information-Preserving Refinement

  Anish Athalye, M. Frans Kaashoek, and Nickolai Zeldovich

  16th USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2022

  Code

• Notary: A Device for Secure Transaction Approval

  Anish Athalye, Adam Belay, M. Frans Kaashoek, Robert Morris, and Nickolai Zeldovich

  27th ACM Symposium on Operating Systems Principles (SOSP), 2019

  Code

• Synthesizing Robust Adversarial Examples

  Anish Athalye, Logan Engstrom, Andrew Ilyas, and Kevin Kwok

  35th International Conference on Machine Learning (ICML), 2018

  Blog Post

• Black-box Adversarial Attacks with Limited Queries and Information

  Andrew Ilyas, Logan Engstrom, Anish Athalye, and Jessy Lin

  35th International Conference on Machine Learning (ICML), 2018

  Blog Post, Code

• Identifying Incorrect Annotations in Multi-Label Classification Data

  Aditya Thyagarajan, Elías Snorrason, Curtis Northcutt, and Jonas Mueller

  ICLR Workshop on Trustworthy ML, 2023

  Code (to run method), Code (to reproduce results), Blog Post

• Detecting Label Errors in Token Classification Data

  Wei-Chen (Eric) Wang and Jonas Mueller

  NeurIPS Workshop on Interactive Learning for Natural Language Processing (InterNLP), 2022

  Code (to run method), Code (to reproduce results), Blog Post

• Back to the Basics: Revisiting Out-of-Distribution Detection Baselines

  Johnson Kuan and Jonas Mueller

  ICML Workshop on Principles of Distribution Shift, 2022

  Code (to run method), Code (to reproduce results), Blog Post

• Model-Agnostic Label Quality Scoring to Detect Real-World Label Errors

  Johnson Kuan and Jonas Mueller

  ICML DataPerf Workshop, 2022

  Code

• Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

  Jiuhai Chen and Jonas Mueller

  Preprint, 2023

• Automated Data Curation for Robust Language Model Fine-Tuning

  Jiuhai Chen and Jonas Mueller

  Preprint, 2024