Cheetah: Bridging the Gap Between Machine Learning and Particle Accelerator Physics with High-Speed, Differentiable Simulations

11 January 2024

Papers citing "Cheetah: Bridging the Gap Between Machine Learning and Particle Accelerator Physics with High-Speed, Differentiable Simulations"

7 / 7 papers shown

Title
Llama 2: Open Foundation and Fine-Tuned Chat Models Hugo Touvron Louis Martin Kevin R. Stone Peter Albert Amjad Almahairi ... Sharan Narang Aurelien Rodriguez Robert Stojnic Sergey Edunov Thomas Scialom AI4MH ALM 309 11,894 0 18 Jul 2023
Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning Jan Kaiser Chenran Xu Annika Eichler Andrea Santamaria Garcia O. Stein ... H. Dinter F. Mayet T. Vinatier F. Burkart H. Schlarb OffRL 39 4 0 06 Jun 2023
High-fidelity Prediction of Megapixel Longitudinal Phase-space Images of Electron Beams using Encoder-Decoder Neural Networks Jun Zhu Ye Chen F. Brinker W. Decking S. Tomin H. Schlarb AI4CE 36 25 0 25 Jan 2021
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 520 42,559 0 03 Dec 2019
Addressing Function Approximation Error in Actor-Critic Methods Scott Fujimoto H. V. Hoof David Meger OffRL 180 5,204 0 26 Feb 2018
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World Joshua Tobin Rachel Fong Alex Ray Jonas Schneider Wojciech Zaremba Pieter Abbeel 257 2,972 0 20 Mar 2017
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas Guibas 3DH 3DPC 3DV PINN 493 14,353 0 02 Dec 2016