- 2023
- Nicolas Gartner, Niels Montanari, Mathieu Richier, Vincent Hugel, Ramprasad Sampath:
Can smoothed particle hydrodynamics simulate physically realistic movements of underwater vehicles? Adv. Robotics 37(20): 1283-1300 (2023) - Jianquan Zhang, Xiao Xiao:
Soft fusion-based cooperative spectrum sensing using particle swarm optimization for cognitive radio networks in cyber-physical systems. Concurr. Comput. Pract. Exp. 35(13) (2023) - Jahanzeb Akhtar, Imran Ghous, Muhammad Jawad, Zhaoxia Duan, Ikramullah Khosa, Saim Ahmed:
A computationally efficient unscented Kalman smoother for ameliorated tracking of subatomic particles in high energy physics experiments. Comput. Phys. Commun. 283: 108585 (2023) - Moisés Arredondo-Velázquez, Lucio Fidel Rebolledo-Herrera, Benito de Celis Alonso, Eduardo Moreno-Barbosa:
Potential Use of State-of-the-Art TDCs for Particle Identification in Particle Physics Experiments. IEEE Instrum. Meas. Mag. 26(6): 13-20 (2023) - Alessio Alexiadis:
A minimalistic approach to physics-informed machine learning using neighbour lists as physics-optimized convolutions for inverse problems involving particle systems. J. Comput. Phys. 473: 111750 (2023) - Nathalie Soybelman, Nilotpal Kakati, Lukas Heinrich, Francesco Armando Di Bello, Etienne Dreyer, Sanmay Ganguly, Eilam Gross, Marumi Kado, Jonathan Shlomi:
Set-conditional set generation for particle physics. Mach. Learn. Sci. Technol. 4(4): 45036 (2023) - Fatma Çakiroglu, Rifat Kurban, Ali Durmus, Ercan Karakose:
Multi-focus image fusion by using swarm and physics based metaheuristic algorithms: a comparative study with archimedes, atomic orbital search, equilibrium, particle swarm, artificial bee colony and jellyfish search optimizers. Multim. Tools Appl. 82(29): 44859-44883 (2023) - Qinghai He, Haowen Zhang, Tianhua Li, Xiaojia Zhang, Xiaoli Li, Chunwang Dong:
NIR Spectral Inversion of Soil Physicochemical Properties in Tea Plantations under Different Particle Size States. Sensors 23(22): 9107 (2023) - Chao Yang, Ruihu Chen, Weida Wang, Ying Li, Xun Shen, Changle Xiang:
Cyber-Physical Optimization-Based Fuzzy Control Strategy for Plug-in Hybrid Electric Buses Using Iterative Modified Particle Swarm Optimization. IEEE Trans. Intell. Veh. 8(5): 3285-3298 (2023) - Milind V. Purohit:
Machine Learning in Particle Physics. BDA (Astronomy, Science, and Engineering) 2023: 128-138 - Sergi Bernet Andrés, Míriam Calvo Gómez, Álvaro García Piquer, Elisabet Golobardes-Ribé, Núria Valls Canudas, Xavier Vilasís-Cardona:
Machine Learning in Particle Physics Experiments: The Case of LHCb. CCIA 2023: 115-119 - Atul Kumar Sinha, Daniele Paliotta, Bálint Máté, John A. Raine, Tobias Golling, François Fleuret:
SUPA: A Lightweight Diagnostic Simulator for Machine Learning in Particle Physics. NeurIPS 2023 - Fady Bishara, Ayan Paul, Jennifer G. Dy:
High-precision regressors for particle physics. CoRR abs/2302.00753 (2023) - Matthew Leigh, Debajyoti Sengupta, Guillaume Quétant, John Andrew Raine, Knut Zoch, Tobias Golling:
PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics. CoRR abs/2303.05376 (2023) - Alexander Shmakov, Alejandro Yankelevich, Jianming Bian, Pierre Baldi:
Interpretable Joint Event-Particle Reconstruction for Neutrino Physics at NOvA with Sparse CNNs and Transformers. CoRR abs/2303.06201 (2023) - Lukas Ehrke, John Andrew Raine, Knut Zoch, Manuel Guth, Tobias Golling:
Topological Reconstruction of Particle Physics Processes using Graph Neural Networks. CoRR abs/2303.13937 (2023) - Zhichao Han, Olga Fink, David S. Kammer:
Collective Relational Inference for learning physics-consistent heterogeneous particle interactions. CoRR abs/2305.00557 (2023) - Steve Abel, Andrei Constantin, Thomas R. Harvey, André Lukas, Luca A. Nutricati:
Decoding Nature with Nature's Tools: Heterotic Line Bundle Models of Particle Physics with Genetic Algorithms and Quantum Annealing. CoRR abs/2306.03147 (2023) - Junn Yong Loo, Ze Yang Ding, Surya Girinatha Nurzaman, Chee-Ming Ting, Vishnu Monn Baskaran, Chee Pin Tan:
Unsupervised Cross-Domain Soft Sensor Modelling via Deep Physics-Inspired Particle Flow Bayes. CoRR abs/2306.04919 (2023) - Masahiko Ueda:
Application of zero-determinant strategies to particle control in statistical physics. CoRR abs/2306.05597 (2023) - Xiangzun Wang, Frank Cichos:
Harnessing Synthetic Active Particles for Physical Reservoir Computing. CoRR abs/2307.15010 (2023) - Alexander Bogatskiy, Timothy Hoffman, David W. Miller, Jan T. Offermann, Xiaoyang Liu:
Explainable Equivariant Neural Networks for Particle Physics: PELICAN. CoRR abs/2307.16506 (2023) - Shikhar Nilabh, Fidel Grandia:
Bayesian Physics-Informed Neural Network for the Forward and Inverse Simulation of Engineered Nano-particles Mobility in a Contaminated Aquifer. CoRR abs/2308.07352 (2023) - Jai Kumar, David Zarzoso, Virginie Grandgirard, Jan Ebert, Stefan Kesselheim:
Physics informed Neural Networks applied to the description of wave-particle resonance in kinetic simulations of fusion plasmas. CoRR abs/2308.12312 (2023) - Alexander Bogatskiy, Timothy Hoffman, Jan T. Offermann:
19 Parameters Is All You Need: Tiny Neural Networks for Particle Physics. CoRR abs/2310.16121 (2023) - Savannah Thais, Daniel Murnane:
Equivariance Is Not All You Need: Characterizing the Utility of Equivariant Graph Neural Networks for Particle Physics Tasks. CoRR abs/2311.03094 (2023) - Vasilis Belis, Patrick Odagiu, Thea Klæboe Årrestad:
Machine Learning for Anomaly Detection in Particle Physics. CoRR abs/2312.14190 (2023) - Nimish Mishra, Kuheli Pratihar, Anirban Chakraborty, Debdeep Mukhopadhyay:
Modelling Delay-based Physically Unclonable Functions through Particle Swarm Optimization. IACR Cryptol. ePrint Arch. 2023: 287 (2023) - 2022
- Mirko Bunse:
Machine learning for acquiring knowledge in astro-particle physics. Technical University of Dortmund, Germany, 2022 - Ewa L. Stepien, Pawel Moskal:
Proceedings for 4th Jagiellonian Symposium on Advances in Particle Physics and Medicine. Bio Algorithms Med Syst. 18(1): 94-95 (2022)