Daniel Ratner - RankMe

33 papers A* 3A 1Journal 24Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Domain Knowledge Guided Bayesian Optimization For Autonomous Alignment Of Complex Scientific Instruments. CoRR Aashwin Mishra, Matt Seaberg, Ryan Roussel, Daniel Ratner, Apurva Mehta
2026	J	`jnl`	Supercharging Simulation-Based Inference for Bayesian Optimal Experimental Design. CoRR Samuel Klein, Willie Neiswanger, Daniel Ratner, Michael Kagan, Sean Gasiorowski
2025	J	`jnl`	A Start To End Machine Learning Approach To Maximize Scientific Throughput From The LCLS-II-HE. CoRR Aashwin Mishra, Matt Seaberg, Ryan Roussel, Frédéric Poitevin, Jana Thayer, Daniel Ratner, Auralee Edelen, Apurva Mehta
2025	—	`conf`	ChatEED: An agentic retrieval assistant for accelerator operators. SC Workshops Aaron Zachary Reed, Claudio Bisegni, Sandesh Shrestha, Michelle Huang, Daniel Ratner
2025	J	`jnl`	Efficient Dynamic and Momentum Aperture Optimization for Lattice Design Using Multipoint Bayesian Algorithm Execution. CoRR Z. Zhang, I. Agapov, Sean Gasiorowski, Thorsten Hellert, Willie Neiswanger, X. Huang, Daniel Ratner
2025	J	`jnl`	Efficient Nudged Elastic Band Method using Neural Network Bayesian Algorithm Execution. CoRR Pranav Kakhandiki, Sathya R. Chitturi, Daniel Ratner, Sean Gasiorowski
2025	J	`jnl`	eLog analysis for accelerators: status and future outlook. CoRR Antonin Sulc, Thorsten Hellert, Aaron Zachary Reed, Adam Carpenter, Alex Bien, Chris Tennant, Claudio Bisegni, Daniel Lersch, Daniel Ratner, David Lawrence, Diana McSpadden, Hayden Hoschouer, Jason St. John, Thomas Britton
2024	J	`jnl`	Coincidence anomaly detection for unsupervised locating of edge localized modes in the DIII-D tokamak dataset. Mach. Learn. Sci. Technol. Finn H. O'Shea, Semin Joung, David R. Smith, Daniel Ratner, Ryan N. Coffee
2024	J	`jnl`	Coincident learning for unsupervised anomaly detection of scientific instruments. Mach. Learn. Sci. Technol. Ryan Humble, Zhe Zhang, Finn H. O'Shea, Eric Darve, Daniel Ratner
2024	J	`jnl`	Differentiable simulation of a liquid argon time projection chamber. Mach. Learn. Sci. Technol. Sean Gasiorowski, Yifan Chen, Youssef S. G. Nashed, Pierre Granger, Camelia Mironov, Ka Vang Tsang, Daniel Ratner, Kazuhiro Terao
2024	J	`jnl`	Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives. Mach. Learn. Sci. Technol. Sara A. Miskovich, Willie Neiswanger, William Colocho, Claudio Emma, Jacqueline Garrahan, Timothy Maxwell, Christopher Mayes, Stefano Ermon, Auralee Edelen, Daniel Ratner
2024	J	`jnl`	Towards Unlocking Insights from Logbooks Using AI. CoRR 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, Kyle J. Hazelwood, Raimund Kammering, Thorsten Hellert, Tim Wilksen, Verena Kain, Wan-Lin Hu
2023	J	`jnl`	Capturing dynamical correlations using implicit neural representations. CoRR Sathya R. Chitturi, Zhurun Ji, Alexander Petsch, Cheng Peng, Zhantao Chen, Rajan Plumley, Mike Dunne, Sougata Mardanya, Sugata Chowdhury, Hongwei Chen, Arun Bansil, Adrian E. Feiguin, Alexander Kolesnikov, Dharmalingam Prabhakaran, Stephen Hayden, Daniel Ratner, Chunjing Jia, Youssef Nashed, Joshua J. Turner
2023	J	`jnl`	Coincident Learning for Unsupervised Anomaly Detection. CoRR Ryan Humble, Zhe Zhang, Finn H. O'Shea, Eric Darve, Daniel Ratner
2023	J	`jnl`	Resilient VAE: Unsupervised Anomaly Detection at the SLAC Linac Coherent Light Source. CoRR Ryan Humble, William Colocho, Finn H. O'Shea, Daniel Ratner, Eric Darve
2022	J	`jnl`	Bayesian Algorithm Execution for Tuning Particle Accelerator Emittance with Partial Measurements. CoRR Sara A. Miskovich, Willie Neiswanger, William Colocho, Claudio Emma, Jacqueline Garrahan, Timothy Maxwell, Christopher Mayes, Stefano Ermon, Auralee Edelen, Daniel Ratner
2022	—	`conf`	CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images. ECCV (21) Axel Levy, Frédéric Poitevin, Julien N. P. Martel, Youssef S. G. Nashed, Ariana Peck, Nina Miolane, Daniel Ratner, Mike Dunne, Gordon Wetzstein
2022	J	`jnl`	CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images. CoRR Axel Levy, Frédéric Poitevin, Julien N. P. Martel, Youssef S. G. Nashed, Ariana Peck, Nina Miolane, Daniel Ratner, Mike Dunne, Gordon Wetzstein
2022	J	`jnl`	Heterogeneous reconstruction of deformable atomic models in Cryo-EM. CoRR Youssef S. G. Nashed, Ariana Peck, Julien N. P. Martel, Axel Levy, Bongjin Koo, Gordon Wetzstein, Nina Miolane, Daniel Ratner, Frédéric Poitevin
2022	J	`jnl`	Implicit Neural Representation as a Differentiable Surrogate for Photon Propagation in a Monolithic Neutrino Detector. CoRR Minjie Lei, Ka Vang Tsang, Sean Gasiorowski, Chuan Li, Youssef S. G. Nashed, Gianluca Petrillo, Olivia Piazza, Daniel Ratner, Kazuhiro Terao
2022	—	`conf`	Performance Variability and Causality in Complex Systems. ACSOS-C Anwesha Das, Daniel Ratner, Alex Aiken
2022	—	`conf`	Testing the data framework for an AI algorithm in preparation for high data rate X-ray facilities. XLOOP@SC Hongwei Chen, Sathya R. Chitturi, Rajan Plumley, Lingjia Shen, Nathan C. Drucker, Nicolas Burdet, Cheng Peng, Sougata Mardanya, Daniel Ratner, Aashwin Mishra, Chun Hong Yoon, Sanghoon Song, Matthieu Chollet, Gilberto Fabbris, Mike Dunne, Silke Nelson, Mingda Li, Aaron Lindenberg, Chunjing Jia, Youssef Nashed, Arun Bansil, Sugata Chowdhury, Adrian E. Feiguin, Joshua J. Turner, Jana Thayer
2021	—	`conf`	CryoPoseNet: End-to-End Simultaneous Learning of Single-particle Orientation and 3D Map Reconstruction from Cryo-electron Microscopy Data. ICCVW Youssef S. G. Nashed, Frédéric Poitevin, Harshit Gupta, Geoffrey Woollard, Michael Kagan, Chun Hong Yoon, Daniel Ratner
2021	J	`jnl`	End-to-End Simultaneous Learning of Single-particle Orientation and 3D Map Reconstruction from Cryo-electron Microscopy Data. CoRR Youssef S. G. Nashed, Frédéric Poitevin, Harshit Gupta, Geoffrey Woollard, Michael Kagan, Chuck Yoon, Daniel Ratner
2020	J	`jnl`	Introduction to Machine Learning for Accelerator Physics. CoRR Daniel Ratner
2020	J	`jnl`	Physics-informed Gaussian Process for Online Optimization of Particle Accelerators. CoRR Adi Hanuka, Xiaobiao Huang, Jane Shtalenkova, Dylan Kennedy, Auralee Edelen, V. R. Lalchand, Daniel Ratner, Joseph Duris
2020	A*	`conf`	Reinforcement Learning for Adaptive Illumination with X-rays. ICRA Jean-Raymond Betterton, Daniel Ratner, Samuel Webb, Mykel J. Kochenderfer
2019	J	`jnl`	Online tuning and light source control using a physics-informed Gaussian process Adi. CoRR Adi Hanuka, Joseph Duris, Jane Shtalenkova, Dylan Kennedy, Auralee Edelen, Daniel Ratner, Xiaobiao Huang
2017	J	`jnl`	Automating, Operationalizing and Productizing Journalistic Article Analysis. CoRR Eric Kingery, Michael S. Manley, Daniel Ratner
2016	A	`conf`	Sparse Gaussian Processes for Bayesian Optimization. UAI Mitchell McIntire, Daniel Ratner, Stefano Ermon
1990	J	`jnl`	NxN Puzzle and Related Relocation Problem. J. Symb. Comput. Daniel Ratner, Manfred K. Warmuth
1986	A*	`conf`	Finding a Shortest Solution for the N × N Extension of the 15-PUZZLE Is Intractable. AAAI Daniel Ratner, Manfred K. Warmuth
1986	A*	`conf`	Joint and LPA*: Combination of Approximation and Search. AAAI Daniel Ratner, Ira Pohl