Joint and LPA*: Combination of Approximation and Search. - Daniel Ratner; Ira Pohl (AAAI, 1986)

Finding a Shortest Solution for the N × N Extension of the 15-PUZZLE Is Intractable. - Daniel Ratner; Manfred K. Warmuth (AAAI, 1986)

NxN Puzzle and Related Relocation Problem. - Daniel Ratner; Manfred K. Warmuth (J. Symb. Comput., 1990)

Sparse Gaussian Processes for Bayesian Optimization. - Mitchell McIntire; Daniel Ratner; Stefano Ermon (UAI, 2016)

Automating, Operationalizing and Productizing Journalistic Article Analysis. - Eric Kingery; Michael S. Manley; Daniel Ratner (CoRR, 2017)

Online tuning and light source control using a physics-informed Gaussian process Adi. - Adi Hanuka; Joseph Duris; Jane Shtalenkova; Dylan Kennedy; Auralee Edelen; Daniel Ratner; Xiaobiao Huang (CoRR, 2019)

Reinforcement Learning for Adaptive Illumination with X-rays. - Jean-Raymond Betterton; Daniel Ratner; Samuel Webb; Mykel J. Kochenderfer (ICRA, 2020)

Introduction to Machine Learning for Accelerator Physics. - Daniel Ratner (CoRR, 2020)

Physics-informed Gaussian Process for Online Optimization of Particle Accelerators. - Adi Hanuka; Xiaobiao Huang; Jane Shtalenkova; Dylan Kennedy; Auralee Edelen; V. R. Lalchand; Daniel Ratner; Joseph Duris (CoRR, 2020)

CryoPoseNet: End-to-End Simultaneous Learning of Single-particle Orientation and 3D Map Reconstruction from Cryo-electron Microscopy Data. - Youssef S. G. Nashed; Frédéric Poitevin; Harshit Gupta; Geoffrey Woollard; Michael Kagan; Chun Hong Yoon; Daniel Ratner (ICCVW, 2021)

End-to-End Simultaneous Learning of Single-particle Orientation and 3D Map Reconstruction from Cryo-electron Microscopy Data. - Youssef S. G. Nashed; Frédéric Poitevin; Harshit Gupta; Geoffrey Woollard; Michael Kagan; Chuck Yoon; Daniel Ratner (CoRR, 2021)

Performance Variability and Causality in Complex Systems. - Anwesha Das 001; Daniel Ratner; Alex Aiken (ACSOS-C, 2022)

CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images. - Axel Levy; Frédéric Poitevin; Julien N. P. Martel; Youssef S. G. Nashed; Ariana Peck; Nina Miolane; Daniel Ratner; Mike Dunne; Gordon Wetzstein (ECCV (21), 2022)

Testing the data framework for an AI algorithm in preparation for high data rate X-ray facilities. - Hongwei Chen; Sathya R. Chitturi; Rajan Plumley; Lingjia Shen; Nathan C. Drucker; Nicolas Burdet; Cheng Peng 012; Sougata Mardanya; Daniel Ratner; Aashwin Mishra; Chun Hong Yoon; Sanghoon Song; et al. (XLOOP@SC, 2022)

Bayesian Algorithm Execution for Tuning Particle Accelerator Emittance with Partial Measurements. - Sara A. Miskovich; Willie Neiswanger; William Colocho; Claudio Emma; Jacqueline Garrahan; Timothy Maxwell; Christopher Mayes; Stefano Ermon; Auralee Edelen; Daniel Ratner (CoRR, 2022)

Heterogeneous reconstruction of deformable atomic models in Cryo-EM. - Youssef S. G. Nashed; Ariana Peck; Julien N. P. Martel; Axel Levy; Bongjin Koo; Gordon Wetzstein; Nina Miolane; Daniel Ratner; Frédéric Poitevin (CoRR, 2022)

Implicit Neural Representation as a Differentiable Surrogate for Photon Propagation in a Monolithic Neutrino Detector. - Minjie Lei; Ka Vang Tsang; Sean Gasiorowski; Chuan Li; Youssef S. G. Nashed; Gianluca Petrillo; Olivia Piazza; Daniel Ratner; Kazuhiro Terao (CoRR, 2022)

Coincident Learning for Unsupervised Anomaly Detection. - Ryan Humble; Zhe Zhang 033; Finn H. O'Shea; Eric Darve; Daniel Ratner (CoRR, 2023)

Capturing dynamical correlations using implicit neural representations. - Sathya R. Chitturi; Zhurun Ji; Alexander Petsch; Cheng Peng 012; Zhantao Chen; Rajan Plumley; Mike Dunne; Sougata Mardanya; Sugata Chowdhury; Hongwei Chen; Arun Bansil; Adrian E. Feiguin; et al. (CoRR, 2023)

Resilient VAE: Unsupervised Anomaly Detection at the SLAC Linac Coherent Light Source. - Ryan Humble; William Colocho; Finn H. O'Shea; Daniel Ratner; Eric Darve (CoRR, 2023)

Towards Unlocking Insights from Logbooks Using AI. - Antonin Sulc; Alex Bien; Annika Eichler; Daniel Ratner; Florian Rehm; Frank Mayet; Gregor Hartmann; Hayden Hoschouer; Henrik Tünnermann; Jan Kaiser; Jason St. John; Jennefer Maldonado; et al. (CoRR, 2024)

Differentiable simulation of a liquid argon time projection chamber. - Sean Gasiorowski; Yifan Chen; Youssef S. G. Nashed; Pierre Granger; Camelia Mironov; Ka Vang Tsang; Daniel Ratner; Kazuhiro Terao (Mach. Learn. Sci. Technol., 2024)

Coincident learning for unsupervised anomaly detection of scientific instruments. - Ryan Humble; Zhe Zhang 033; Finn H. O'Shea; Eric Darve; Daniel Ratner (Mach. Learn. Sci. Technol., 2024)

Coincidence anomaly detection for unsupervised locating of edge localized modes in the DIII-D tokamak dataset. - Finn H. O'Shea; Semin Joung; David R. Smith; Daniel Ratner; Ryan N. Coffee (Mach. Learn. Sci. Technol., 2024)

Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives. - Sara A. Miskovich; Willie Neiswanger; William Colocho; Claudio Emma; Jacqueline Garrahan; Timothy Maxwell; Christopher Mayes; Stefano Ermon; Auralee Edelen; Daniel Ratner (Mach. Learn. Sci. Technol., 2024)

A Start To End Machine Learning Approach To Maximize Scientific Throughput From The LCLS-II-HE. - Aashwin Mishra; Matt Seaberg; Ryan Roussel; Frédéric Poitevin; Jana Thayer; Daniel Ratner; Auralee Edelen; Apurva Mehta (CoRR, 2025)

eLog analysis for accelerators: status and future outlook. - Antonin Sulc; Thorsten Hellert; Aaron Reed; Adam Carpenter; Alex Bien; Chris Tennant; Claudio Bisegni; Daniel Lersch; Daniel Ratner; David Lawrence; Diana McSpadden; Hayden Hoschouer; et al. (CoRR, 2025)