AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models. - Karl Krauth; Edwin V. Bonilla; Kurt Cutajar; Maurizio Filippone (UAI, 2017)

numpywren: serverless linear algebra. - Vaishaal Shankar; Karl Krauth; Qifan Pu; Eric Jonas; Shivaram Venkataraman; Ion Stoica; Benjamin Recht; Jonathan Ragan-Kelley (CoRR, 2018)

Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator. - Karl Krauth; Stephen Tu; Benjamin Recht (NeurIPS, 2019)

Cloud Programming Simplified: A Berkeley View on Serverless Computing. - Eric Jonas; Johann Schleier-Smith; Vikram Sreekanti; Chia-Che Tsai; Anurag Khandelwal; Qifan Pu; Vaishaal Shankar; João Carreira; Karl Krauth; Neeraja Jayant Yadwadkar; Joseph E. Gonzalez; Raluca Ada Popa; et al. (CoRR, 2019)

Generic Inference in Latent Gaussian Process Models. - Edwin V. Bonilla; Karl Krauth; Amir Dezfouli (J. Mach. Learn. Res., 2019)

Serverless linear algebra. - Vaishaal Shankar; Karl Krauth; Kailas Vodrahalli; Qifan Pu; Benjamin Recht; Ion Stoica; Jonathan Ragan-Kelley; Eric Jonas; Shivaram Venkataraman (SoCC, 2020)

The Effect of Natural Distribution Shift on Question Answering Models. - John Miller 001; Karl Krauth; Benjamin Recht; Ludwig Schmidt (ICML, 2020)

Exploration in two-stage recommender systems. - Jiri Hron; Karl Krauth; Michael I. Jordan; Niki Kilbertus (CoRR, 2020)

Do Offline Metrics Predict Online Performance in Recommender Systems? - Karl Krauth; Sarah Dean; Alex Zhao; Wenshuo Guo; Mihaela Curmei; Benjamin Recht; Michael I. Jordan (CoRR, 2020)

The Stereotyping Problem in Collaboratively Filtered Recommender Systems. - Wenshuo Guo; Karl Krauth; Michael I. Jordan; Nikhil Garg 001 (EAAMO, 2021)

On Component Interactions in Two-Stage Recommender Systems. - Jiri Hron; Karl Krauth; Michael I. Jordan; Niki Kilbertus (NeurIPS, 2021)

Breaking Feedback Loops in Recommender Systems with Causal Inference. - Karl Krauth; Yixin Wang 002; Michael I. Jordan (CoRR, 2022)

The Dynamics of Recommender Systems - Karl Krauth (2022)

Recommendation Systems with Distribution-Free Reliability Guarantees. - Anastasios N. Angelopoulos; Karl Krauth; Stephen Bates; Yixin Wang 002; Michael I. Jordan (COPA, 2023)

Modeling content creator incentives on algorithm-curated platforms. - Jiri Hron; Karl Krauth; Michael I. Jordan; Niki Kilbertus; Sarah Dean (ICLR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)