Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
Marta Skreta
Tara Akhound-Sadegh
Viktor Ohanesian
Roberto Bondesan
Alan Aspuru-Guzik
Arnaud Doucet
Rob Brekelmans
Alexander Tong
Kirill Neklyudov
While score-based generative models are the model of choice across diverse domains, there are limited tools available for controlling infere… (voir plus)nce-time behavior in a principled manner, e.g. for composing multiple pretrained models. Existing classifier-free guidance methods use a simple heuristic to mix conditional and unconditional scores to approximately sample from conditional distributions. However, such methods do not approximate the intermediate distributions, necessitating additional 'corrector' steps. In this work, we provide an efficient and principled method for sampling from a sequence of annealed, geometric-averaged, or product distributions derived from pretrained score-based models. We derive a weighted simulation scheme which we call Feynman-Kac Correctors (FKCs) based on the celebrated Feynman-Kac formula by carefully accounting for terms in the appropriate partial differential equations (PDEs). To simulate these PDEs, we propose Sequential Monte Carlo (SMC) resampling algorithms that leverage inference-time scaling to improve sampling quality. We empirically demonstrate the utility of our methods by proposing amortized sampling via inference-time temperature annealing, improving multi-objective molecule generation using pretrained models, and improving classifier-free guidance for text-to-image generation. Our code is available at https://github.com/martaskrt/fkc-diffusion.
2025-03-04
ArXiv (prépublication)
arxiv.org
arxiv.org
Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
Marta Skreta
Tara Akhound-Sadegh
Viktor Ohanesian
Roberto Bondesan
Alan Aspuru-Guzik
Arnaud Doucet
Rob Brekelmans
Alexander Tong
Kirill Neklyudov
While score-based generative models are the model of choice across diverse domains, there are limited tools available for controlling infere… (voir plus)nce-time behavior in a principled manner, e.g. for composing multiple pretrained models. Existing classifier-free guidance methods use a simple heuristic to mix conditional and unconditional scores to approximately sample from conditional distributions. However, such methods do not approximate the intermediate distributions, necessitating additional 'corrector' steps. In this work, we provide an efficient and principled method for sampling from a sequence of annealed, geometric-averaged, or product distributions derived from pretrained score-based models. We derive a weighted simulation scheme which we call Feynman-Kac Correctors (FKCs) based on the celebrated Feynman-Kac formula by carefully accounting for terms in the appropriate partial differential equations (PDEs). To simulate these PDEs, we propose Sequential Monte Carlo (SMC) resampling algorithms that leverage inference-time scaling to improve sampling quality. We empirically demonstrate the utility of our methods by proposing amortized sampling via inference-time temperature annealing, improving multi-objective molecule generation using pretrained models, and improving classifier-free guidance for text-to-image generation. Our code is available at https://github.com/martaskrt/fkc-diffusion.
2025-03-04
ArXiv (prépublication)
arxiv.org
arxiv.org
Hardware Synthesizable Exceptions using Continuations
Paul Teng
Christophe Dubach
2025-03-04
Proceedings of the 30th Asia and South Pacific Design Automation Conference (publié)
doi.org
LLM-Safety Evaluations Lack Robustness
Tim Beyer
Sophie Xhonneux
Simon Geisler
Gauthier Gidel
Leo Schwinn
Stephan Günnemann
In this paper, we argue that current safety alignment research efforts for large language models are hindered by many intertwined sources of… (voir plus) noise, such as small datasets, methodological inconsistencies, and unreliable evaluation setups. This can, at times, make it impossible to evaluate and compare attacks and defenses fairly, thereby slowing progress. We systematically analyze the LLM safety evaluation pipeline, covering dataset curation, optimization strategies for automated red-teaming, response generation, and response evaluation using LLM judges. At each stage, we identify key issues and highlight their practical impact. We also propose a set of guidelines for reducing noise and bias in evaluations of future attack and defense papers. Lastly, we offer an opposing perspective, highlighting practical reasons for existing limitations. We believe that addressing the outlined problems in future research will improve the field's ability to generate easily comparable results and make measurable progress.
2025-03-04
ArXiv (prépublication)
arxiv.org
arxiv.org
LLM-Safety Evaluations Lack Robustness
Tim Beyer
Sophie Xhonneux
Simon Geisler
Gauthier Gidel
Leo Schwinn
Stephan Günnemann
In this paper, we argue that current safety alignment research efforts for large language models are hindered by many intertwined sources of… (voir plus) noise, such as small datasets, methodological inconsistencies, and unreliable evaluation setups. This can, at times, make it impossible to evaluate and compare attacks and defenses fairly, thereby slowing progress. We systematically analyze the LLM safety evaluation pipeline, covering dataset curation, optimization strategies for automated red-teaming, response generation, and response evaluation using LLM judges. At each stage, we identify key issues and highlight their practical impact. We also propose a set of guidelines for reducing noise and bias in evaluations of future attack and defense papers. Lastly, we offer an opposing perspective, highlighting practical reasons for existing limitations. We believe that addressing the outlined problems in future research will improve the field's ability to generate easily comparable results and make measurable progress.
2025-03-04
ArXiv (prépublication)
arxiv.org
arxiv.org
Variation Matters: from Mitigating to Embracing Zero-Shot NAS Ranking Function Variation
Pavel Rumiantsev
Mark Coates
Neural Architecture Search (NAS) is a powerful automatic alternative to manual design of a neural network. In the zero-shot version, a fast … (voir plus)ranking function is used to compare architectures without training them. The outputs of the ranking functions often vary significantly due to different sources of randomness, including the evaluated architecture's weights' initialization or the batch of data used for calculations. A common approach to addressing the variation is to average a ranking function output over several evaluations. We propose taking into account the variation in a different manner, by viewing the ranking function output as a random variable representing a proxy performance metric. During the search process, we strive to construct a stochastic ordering of the performance metrics to determine the best architecture. Our experiments show that the proposed stochastic ordering can effectively boost performance of a search on standard benchmark search spaces.
2025-03-04
TMLR (accepté)
doi.org
openreview.net
Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study.
Shayan Nejadshamsi
Vania Karami
Negar Ghourchian
Narges Armanfard
Howard Bergman
Roland Grad
Machelle Wilchesky
Vladimir Khanassov
Isabelle Vedel
Samira Abbasgholizadeh-Rahimi
BACKGROUND Depression, characterized by persistent sadness and loss of interest in daily activities, greatly reduces quality of life. Early … (voir plus)detection is vital for effective treatment and intervention. While many studies use wearable devices to classify depression based on physical activity, these often rely on intrusive methods. Additionally, most depression classification studies involve large participant groups and use single-stage classifiers without explainability. OBJECTIVE This study aims to assess the feasibility of classifying depression using nonintrusive Wi-Fi-based motion sensor data using a novel machine learning model on a limited number of participants. We also conduct an explainability analysis to interpret the model's predictions and identify key features associated with depression classification. METHODS In this study, we recruited adults aged 65 years and older through web-based and in-person methods, supported by a McGill University health care facility directory. Participants provided consent, and we collected 6 months of activity and sleep data via nonintrusive Wi-Fi-based sensors, along with Edmonton Frailty Scale and Geriatric Depression Scale data. For depression classification, we proposed a HOPE (Home-Based Older Adults' Depression Prediction) machine learning model with feature selection, dimensionality reduction, and classification stages, evaluating various model combinations using accuracy, sensitivity, precision, and F1-score. Shapely addictive explanations and local interpretable model-agnostic explanations were used to explain the model's predictions. RESULTS A total of 6 participants were enrolled in this study; however, 2 participants withdrew later due to internet connectivity issues. Among the 4 remaining participants, 3 participants were classified as not having depression, while 1 participant was identified as having depression. The most accurate classification model, which combined sequential forward selection for feature selection, principal component analysis for dimensionality reduction, and a decision tree for classification, achieved an accuracy of 87.5%, sensitivity of 90%, and precision of 88.3%, effectively distinguishing individuals with and those without depression. The explainability analysis revealed that the most influential features in depression classification, in order of importance, were "average sleep duration," "total number of sleep interruptions," "percentage of nights with sleep interruptions," "average duration of sleep interruptions," and "Edmonton Frailty Scale." CONCLUSIONS The findings from this preliminary study demonstrate the feasibility of using Wi-Fi-based motion sensors for depression classification and highlight the effectiveness of our proposed HOPE machine learning model, even with a small sample size. These results suggest the potential for further research with a larger cohort for more comprehensive validation. Additionally, the nonintrusive data collection method and model architecture proposed in this study offer promising applications in remote health monitoring, particularly for older adults who may face challenges in using wearable devices. Furthermore, the importance of sleep patterns identified in our explainability analysis aligns with findings from previous research, emphasizing the need for more in-depth studies on the role of sleep in mental health, as suggested in the explainable machine learning study.
2025-03-03
JMIR Aging (publié)
doi.org
Interval Regression: A Comparative Study with Proposed Models
Tung L. Nguyen
Toby Dylan Hocking
Regression models are essential for a wide range of real-world applications. However, in practice, target values are not always precisely kn… (voir plus)own; instead, they may be represented as intervals of acceptable values. This challenge has led to the development of Interval Regression models. In this study, we provide a comprehensive review of existing Interval Regression models and introduce alternative models for comparative analysis. Experiments are conducted on both real-world and synthetic datasets to offer a broad perspective on model performance. The results demonstrate that no single model is universally optimal, highlighting the importance of selecting the most suitable model for each specific scenario.
2025-03-03
ArXiv (prépublication)
arxiv.org
arxiv.org
Interval Regression: A Comparative Study with Proposed Models
Tung L. Nguyen
Toby Dylan Hocking
Regression models are essential for a wide range of real-world applications. However, in practice, target values are not always precisely kn… (voir plus)own; instead, they may be represented as intervals of acceptable values. This challenge has led to the development of Interval Regression models. In this study, we provide a comprehensive review of existing Interval Regression models and introduce alternative models for comparative analysis. Experiments are conducted on both real-world and synthetic datasets to offer a broad perspective on model performance. The results demonstrate that no single model is universally optimal, highlighting the importance of selecting the most suitable model for each specific scenario.
2025-03-03
ArXiv (prépublication)
arxiv.org
arxiv.org
Platform-based Adaptive Experimental Research in Education: Lessons Learned from The Digital Learning Challenge
Ilya Musabirov
Mohi Reza
Haochen Song
Steven Moore
Pan Chen
Harsh Kumar
Tong Li
John Stamper
Norman Bier
Anna Rafferty
Thomas Price
Nina Deliu
Audrey Durand
Michael Liut
Joseph Jay Williams
: We report on our experience with a real-world, multi-experimental evaluation of an adaptive experimentation platform within the XPRIZE Dig… (voir plus)ital Learning Challenge framework. We showcase how EASI (Experiment as a Service) cross-platform software supports quick integration and deployment of adaptive experiments as well as five systematic replications within a 30-day timeframe. The outline the key scenarios of the applicability of platform-supported experiments and reflect on lessons learned from this two-year project that can help researchers and practitioners to integrate adaptive experiments in real-world courses
2025-03-03
Proceedings of the 15th International Learning Analytics and Knowledge Conference (publié)
doi.org
Simulation of the Background from $^{13}$C$(\alpha, n)^{16}$O Reaction in the JUNO Scintillator
Juno Collaboration Thomas Adam
Kai Adamowicz
Shakeel Ahmad
Rizwan Ahmed
Sebastiano Aiello
Fengpeng An
C. Andreopoulos
Giuseppe Andronico
Nikolay Anfimov
Vito Antonelli
Tatiana Antoshkina
João Pedro Athayde Marcondes de André
Didier Auguste
Weidong Bai
Nikita Balashov
Andrea Barresi
Davide Basilico
Eric Baussan
Marco Beretta
Antonio Bergnoli … (voir 478 de plus)
Nikita Bessonov
Daniel Bick
Lukas Bieger
Svetlana Biktemerova
Thilo Birkenfeld
Simon Blyth
Anastasia Bolshakova
Mathieu Bongrand
Matteo Borghesi
Dominique Breton
Augusto Brigatti
Riccardo Brugnera
Riccardo Bruno
Marcel Buchner
Antonio Budano
Jose Busto
Anatael Cabrera
Barbara Caccianiga
Hao Cai
Xiao Cai
Yanke Cai
Z. Cai
Stéphane Callier
Steven Calvez
Antonio Cammi
C. Cao
Guofu Cao
Jun Cao
Yaoqi Cao
Rossella Caruso
Cédric Cerna
Vanessa Cerrone
Jinfan Chang
Yunling Chang
Auttakit Chatrabhuti
Chao Chen
Guoming Chen
Jiahui Chen
Jian Chen
Jing Chen
Junyou Chen
Pingping Chen
Shaomin Chen
Shiqiang Chen
Xin Chen
Yiming Chen
Yixue Chen
Yu Chen
Ze Chen
Zhangming Chen
Zhiyuan Chen
Jie Cheng
Yaping Cheng
Yuanyuan Zhang
Alexander Chepurnov
Alexey Chetverikov
Davide Chiesa
Pietro Chimenti
Po-Lin Chou
Ziliang Chu
Artem Chukanov
Gérard Claverie
Catia Clementi
Barbara Clerbaux
C. Coletta
Selma Conforti Di Lorenzo
Simon Csakli
Chenyang Cui
Olivia Dalager
C. Taille
Zhi Deng
Ziyan Deng
Xiaoyu Ding
Xuefeng Ding
Yayun Ding
Bayu Dirgantara
Carsten Dittrich
Sergey Dmitrievsky
David Doerflinger
Dmitry Dolzhikov
Haojie Dong
Jianmeng Dong
Evgeny Doroshkevich
Marcos Dracos
Frédéric Druillole
Ran Du
Shuxian Du
Yujie Duan
K. Dugas
Stefano Dusini
Hongyue Duyang
J. Eck
Timo Enqvist
Andrea Fabbri
Ulrike Fahrendholz
Lei Fan
Jian Fang
W. Fang
Dmitry Fedoseev
Li-Cheng Feng
Qichun Feng
Federico Ferraro
Daniela Fetzer
Marcellin Fotz'e
Amélie Fournier
Aaron Freegard
Feng Gao
Alberto Garfagnini
Arsenii Gavrikov
Marco Giammarchi
Nunzio Giudice
Maxim Gonchar
Guanghua Gong
Hui Gong
Yuri Gornushkin
Marco Grassi
Maxim Gromov
Vasily Gromov
Minghao Gu
X. Gu
Yunting Gu
M. Guan
Yuduo Guan
Nunzio Guardone
Rosa Maria Guizzetti
Cong Guo
Wanlei Guo
Caren Hagner
Hechong Han
Ran Han
Yang Han
Jinhong He
Miao He
Wei He
Xinhai He
Ziou He
Tobias Heinz
Patrick Hellmuth
Yuekun Heng
Y. Hor
Shaojing Hou
Yee Hsiung
Bei-Zhen Hu
Hang Hu
Jun Hu
T. Hu
Yuxiang Hu
Guihong Huang
Jinhao Huang
Jun-Hao Huang
K. Huang
Shengheng Huang
Tao Huang
Xingtao Huang
Yongbo Huang
Jiaqi Hui
Lei Huo
Cédric Huss
Safeer Hussain
Leonard Imbert
Ara Ioannisian
Adrienne Jacobi
Arshak Jafar
Beatrice Jelmini
Xiangpan Ji
Xiaolu Ji
Huihui Jia
Junji Jia
Cailian Jiang
Wei Jiang
Xiaoshan Jiang
Xiaozhao Jiang
Yi-Nong Jiang
Yixuan Jiang
Xiao-Ying Jing
Cécile Jollet
Li Kang
Rebin Karaparabil
Narine Kazarian
Ali Khan
Amina Khatun
Khanchai Khosonthongkee
Denis Korablev
Konstantin Kouzakov
Alexey Krasnoperov
Sergey Kuleshov
S. Kumaran
Nikolay Kutovskiy
Loïc Labit
Tobias Lachenmaier
Haojing Lai
Cecilia Landini
Sébastien Leblanc
M. Lecocq
Frederic Lefevre
Rui Li
Rupert Leitner
Jason Leung
Demin Li
Yi Wang
Fule Li
Gaosong Li
Hongjian Li
Huang Li
Jiajun Li
Min Li
Nan Li
Qingjiang Li
Ruhui Li
Ruiting Lei
Shanfeng Li
Tao Li
Teng Li
Weidong Li
Xiaonan Li
Yi Li
Yichen Li
Yifan Li
Yufeng Li
Zhaohan Li
Zhibing Li
Zifeng Li
Zonghai Li
An-An Liang
Jiajun Liao
Minghua Liao
Yilin Liao
Ayut Limphirat
Bo-Chun Lin
Guey-Lin Lin
Shengxin Lin
Tao Lin
Xianhao Lin
Xingyi Lin
Jiajie Ling
Xin Ling
Ivano Lippi
Caimei Liu
Fang Liu
Feng Liu
Haidong Liu
Haotian Liu
Hongbang Liu
Hongjuan Liu
Hongtao Liu
Hongyang Liu
Jianglai Liu
Jiaxi Liu
Jinchang Liu
Kainan Liu
Min Liu
Qian Liu
Runxuan Liu
Shenghui Liu
Shulin Liu
Xiaowei Liu
Xiwen Liu
Xuewei Liu
Yankai Liu
Zhen Liu
Lorenzo Loi
Alexey Lokhov
Paolo Lombardi
Claudio Lombardo
Kai Loo
Haoqi Lu
Junguang Lu
Meishu Lu
Peizhi Lu
Shu-Min Lu
Xianguo Lu
Bayarto Lubsandorzhiev
Sultim Lubsandorzhiev
Livia Ludhova
Arslan Lukanov
F. Luo
Guang Luo
Jianyi Luo
Shu Luo
Wuming Luo
Xiaojie Luo
Vladimir Lyashuk
Bangzheng Ma
Bing Ma
Q. Ma
Si Ma
W.Y. Ma
Xiaoyan Ma
Xubo Ma
Jihane Maalmi
Jingyu Mai
Marco Malabarba
Yury Malyshkin
Roberto Carlos Mandujano
Fabio Mantovani
Xin Mao
S. M. Mari
Agnese Martini
Matthias Mayer
Davit Mayilyan
Yu Meng
Anselmo Meregaglia
Lino Miramonti
Marta Colomer Molla
Michele Montuschi
Cristobal Morales Reveco
Iwan Morton-blake
M. Nastasi
Dmitry V. Naumov
Elena Naumova
Igor Nemchenok
Elisabeth Neuerburg
Minh Thuan Nguyen Thi
Alexey Nikolaev
F. Ning
Zhe Ning
Yujie Niu
Hiroshi Nunokawa
Juan Pedro Ochoa-Ricoux
Sebastian Olivares
Alexander Olshevskiy
Domizia Orestano
Fausto Ortica
Rainer Othegraven
Yifei Pan
A. Paoloni
George Parker
Y. Pei
Luca Pelicci
Anguo Peng
Yuefeng Peng
Zhaoyuan Peng
Elisa Percalli
Willy Perrin
Frédéric Perrot
P. Petitjean
Fabrizio Petrucci
Oliver Pilarczyk
Artyom Popov
Pascal Poussot
Ezio Previtali
F. Qi
M. Qi
Xiaohui Qi
Sen Qian
X. Qian
Zhonghua Qin
S. Qiu
Manhao Qu
Zhe Qu
Gioacchino Ranucci
Thomas Raymond
A. Re
Abdel Rebii
Mariia Redchuk
Bin Ren
Yuhan Ren
Barbara Ricci
Komkrit Rientong
Mariam Rifai
Mathieu Roche
Narongkiat Rodphai
Fernanda de Faria Rodrigues
Aldo Romani
Bedřich Roskovec
Arseniy Rybnikov
Andrey Sadovsky
Paolo Saggese
Deshan Sandanayake
Anut Sangka
G. Sava
Utane Sawangwit
Michaela Schever
Cédric Schwab
Konstantin Schweizer
Alexandr Selyunin
Andrea Serafini
M. Settimo
Junyu Shao
V. Sharov
Hangyu Shi
Hexi Shi
Jingyang Shi
Yanan Shi
Vitaly Shutov
Andrey Sidorenkov
Fedor Šimkovic
Apeksha Singhal
Chiara Sirignano
Jaruchit Siripak
Monica Sisti
Oleg Smirnov
Sergey Sokolov
Julanan Songwadhana
Boonrucksar Soonthornthum
Albert Sotnikov
Warintorn Sreethawong
Achim Stahl
Luca Stanco
E. S. Farilla
Konstantin Stankevich
Hans Steiger
Jochen Steinmann
Tobias Sterr
Virginia Strati
Mikhail Strizh
Alexander Studenikin
Aoqi Su
Jun Su
Guangbao Sun
Mingxia Sun
Shifeng Sun
Xilei Sun
Yongzhao Sun
Zhengyang Sun
Narumon Suwonjandee
Akira Takenaka
Xiaohan Tan
Jian Tang
Jingzhe Tang
Qiang Tang
Quan Tang
Xiaodong Tang
Vidhya Thara Hariharan
Yuxin Tian
Igor Tkachev
Tomas Tmej
M. Torri
Andrea Triossi
Wladyslaw Trzaska
Yu-Chen Tung
Cristina Tuve
Nikita Ushakov
Carlo Venettacci
Giuseppe Verde
Maxim Vialkov
Benoit Viaud
Cornelius Moritz Vollbrecht
Vit Vorobel
Dmitriy Voronin
Lucia Votano
Caishen Wang
Chung-Hsiang Wang
En Wang
Hanwen Wang
Jiabin Wang
Jun Wang
Li Wang
Meng Wang
Mingyuan Wang
Qianchuan Wang
Ruiguang Wang
Sibo Wang
Tianhong Wang
Wei Wang
Wenshuai Wang
Xi Wang
Yangfu Wang
Yaoguang Wang
Yifang Wang
Yuan Wang
Yuyi Wang
Zhe Wang
Zheng Wang
Zhimin Wang
Apimook Watcharangkool
Wei Wei
Yadong Wei
Yuehuan Wei
Zhengbao Wei
Kaile Wen
Jun Weng
Christopher Wiebusch
Rosmarie Wirth
Bi Wu
Chengxin Wu
Diru Wu
Qun Wu
Large-scale organic liquid scintillator detectors are highly efficient in the detection of MeV-scale electron antineutrinos. These signal ev… (voir plus)ents can be detected through inverse beta decay on protons, which produce a positron accompanied by a neutron. A noteworthy background for antineutrinos coming from nuclear power reactors and from the depths of the Earth (geoneutrinos) is generated by (
2025-03-02
ArXiv (prépublication)
arxiv.org
arxiv.org
Simulation of the Background from $^{13}$C$(\alpha, n)^{16}$O Reaction in the JUNO Scintillator
Juno Collaboration Thomas Adam
Kai Adamowicz
Shakeel Ahmad
Rizwan Ahmed
Sebastiano Aiello
Fengpeng An
C. Andreopoulos
Giuseppe Andronico
Nikolay Anfimov
Vito Antonelli
Tatiana Antoshkina
João Pedro Athayde Marcondes de André
Didier Auguste
Weidong Bai
Nikita Balashov
Andrea Barresi
Davide Basilico
Eric Baussan
Marco Beretta
Antonio Bergnoli … (voir 480 de plus)
Nikita Bessonov
Daniel Bick
Lukas Bieger
Svetlana Biktemerova
Thilo Birkenfeld
Simon Blyth
Anastasia Bolshakova
Mathieu Bongrand
Matteo Borghesi
Dominique Breton
Augusto Brigatti
Riccardo Brugnera
Riccardo Bruno
Marcel Buchner
Antonio Budano
Jose Busto
Anatael Cabrera
Barbara Caccianiga
Hao Cai
Xiao Cai
Yanke Cai
Z. Cai
Stéphane Callier
Steven Calvez
Antonio Cammi
C. Cao
Guofu Cao
Jun Cao
Yaoqi Cao
Rossella Caruso
Cédric Cerna
Vanessa Cerrone
Jinfan Chang
Yunling Chang
Auttakit Chatrabhuti
Chao Chen
Guoming Chen
Jiahui Chen
Jian Chen
Jing Chen
Junyou Chen
Pingping Chen
Shaomin Chen
Shiqiang Chen
Xin Chen
Yiming Chen
Yixue Chen
Yu Chen
Ze Chen
Zhangming Chen
Zhiyuan Chen
Jie Cheng
Yaping Cheng
Yuanyuan Zhang
Alexander Chepurnov
Alexey Chetverikov
Davide Chiesa
Pietro Chimenti
Po-Lin Chou
Ziliang Chu
Artem Chukanov
Gérard Claverie
Catia Clementi
Barbara Clerbaux
C. Coletta
Selma Conforti Di Lorenzo
Simon Csakli
Chenyang Cui
Olivia Dalager
C. Taille
Zhi Deng
Ziyan Deng
Xiaoyu Ding
Xuefeng Ding
Yayun Ding
Bayu Dirgantara
Carsten Dittrich
Sergey Dmitrievsky
David Doerflinger
Dmitry Dolzhikov
Haojie Dong
Jianmeng Dong
Evgeny Doroshkevich
Marcos Dracos
Frédéric Druillole
Ran Du
Shuxian Du
Yujie Duan
K. Dugas
Stefano Dusini
Hongyue Duyang
J. Eck
Timo Enqvist
Andrea Fabbri
Ulrike Fahrendholz
Lei Fan
Jian Fang
W. X. Fang
Dmitry Fedoseev
Li-Cheng Feng
Qichun Feng
Federico Ferraro
Daniela Fetzer
Marcellin Fotz'e
Amélie Fournier
Aaron Freegard
Feng Gao
Alberto Garfagnini
Arsenii Gavrikov
Marco Giammarchi
Nunzio Giudice
Maxim Gonchar
Guanghua Gong
Hui Gong
Yuri Gornushkin
Marco Grassi
Maxim Gromov
Vasily Gromov
Minghao Gu
X. Gu
Yunting Gu
M. Guan
Yuduo Guan
Nunzio Guardone
Rosa Maria Guizzetti
Cong Guo
Wanlei Guo
Caren Hagner
Hechong Han
Ran Han
Yang Han
Jinhong He
Miao He
Wei He
Xinhai He
Ziou He
Tobias Heinz
Patrick Hellmuth
Yuekun Heng
Y. Hor
Shaojing Hou
Yee Hsiung
Bei-Zhen Hu
Hang Hu
Jun Hu
T. Hu
Yuxiang Hu
Guihong Huang
Jinhao Huang
Jun-Hao Huang
Kai-Zhao Huang
Shengheng Huang
Tao Huang
Xingtao Huang
Yongbo Huang
Jiaqi Hui
Lei Huo
Cédric Huss
Safeer Hussain
Leonard Imbert
Ara Ioannisian
Adrienne Jacobi
Arshak Jafar
Beatrice Jelmini
Xiangpan Ji
Xiaolu Ji
Huihui Jia
Junji Jia
Cailian Jiang
Wei Jiang
Xiaoshan Jiang
Xiaozhao Jiang
Yi-Nong Jiang
Yixuan Jiang
Xiao-Ying Jing
Cécile Jollet
Li Kang
Rebin Karaparabil
Narine Kazarian
Ali Khan
Amina Khatun
Khanchai Khosonthongkee
Denis Korablev
Konstantin Kouzakov
Alexey Krasnoperov
Sergey Kuleshov
S. Kumaran
Nikolay Kutovskiy
Loïc Labit
Tobias Lachenmaier
Haojing Lai
Cecilia Landini
Sébastien Leblanc
M. Lecocq
Frederic Lefevre
Rui Li
Rupert Leitner
Jason Leung
Demin Li
Fule Li
Gaosong Li
Hongjian Li
Huang Li
Jiajun Li
Min Li
Nan Li
Qingjiang Li
Ruhui Li
Ruiting Lei
Shanfeng Li
Tao Li
Teng Li
Weidong Li
Xiaonan Li
Yi Li
Yichen Li
Yifan Li
Yufeng Li
Zhaohan Li
Zhibing Li
Zifeng Li
Zonghai Li
An-An Liang
Jiajun Liao
Minghua Liao
Yilin Liao
Ayut Limphirat
Bohan Lin
Guey-Lin Lin
Shengxin Lin
Tao Lin
Xianhao Lin
Xingyi Lin
Jiajie Ling
Xin Ling
Ivano Lippi
Caimei Liu
Yang Liu
Feng Liu
Haidong Liu
Haotian Liu
Hongbang Liu
Hongjuan Liu
Hongtao Liu
Hongyang Liu
Jianglai Liu
Jiaxi Liu
Jinchang Liu
Kainan Liu
Min Liu
Qian Liu
Runxuan Liu
Shenghui Liu
Shulin Liu
Xiaowei Liu
Xiwen Liu
Xuewei Liu
Yankai Liu
Zhen Liu
Lorenzo Loi
Alexey Lokhov
Paolo Lombardi
Claudio Lombardo
Kai Loo
Haoqi Lu
Junguang Lu
Meishu Lu
Peizhi Lu
Shu-Min Lu
Xianguo Lu
Bayarto Lubsandorzhiev
Sultim Lubsandorzhiev
Livia Ludhova
Arslan Lukanov
F. Luo
Guang Luo
Jianyi Luo
Shu Luo
Wuming Luo
Xiaojie Luo
Vladimir Lyashuk
B. Ma
Bangzheng Ma
Bing Ma
R. Q. Ma
Si Ma
W.Y. Ma
Xiaoyan Ma
Xubo Ma
Jihane Maalmi
Jingyu Mai
Marco Malabarba
Yury Malyshkin
Roberto Carlos Mandujano
Fabio Mantovani
Xin Mao
S. M. Mari
Agnese Martini
Matthias Mayer
Davit Mayilyan
Yu Meng
Anselmo Meregaglia
Lino Miramonti
Marta Colomer Molla
Michele Montuschi
Cristobal Morales Reveco
Iwan Morton-blake
M. Nastasi
Dmitry V. Naumov
Elena Naumova
Igor Nemchenok
Elisabeth Neuerburg
Minh Thuan Nguyen Thi
Alexey Nikolaev
F. Ning
Zhe Ning
Yujie Niu
Hiroshi Nunokawa
Juan Pedro Ochoa-Ricoux
Sebastian Olivares
Alexander Olshevskiy
Domizia Orestano
Fausto Ortica
Rainer Othegraven
Yifei Pan
A. Paoloni
George Parker
Y. P. Pei
Luca Pelicci
Anguo Peng
Yuefeng Peng
Zhaoyuan Peng
Z-R Peng
Elisa Percalli
Willy Perrin
Frédéric Perrot
P. Petitjean
Fabrizio Petrucci
Oliver Pilarczyk
Artyom Popov
Pascal Poussot
Ezio Previtali
F. Qi
M. Qi
Xiaohui Qi
Sen Qian
X. Qian
Zhonghua Qin
S. Qiu
Manhao Qu
Zhe Qu
Gioacchino Ranucci
Thomas Raymond
A. Re
Abdel Rebii
Mariia Redchuk
Bin Ren
Yuhan Ren
Barbara Ricci
Komkrit Rientong
Mariam Rifai
Mathieu Roche
Narongkiat Rodphai
Fernanda de Faria Rodrigues
Aldo Romani
Bedřich Roskovec
Arseniy Rybnikov
Andrey Sadovsky
Paolo Saggese
Deshan Sandanayake
Anut Sangka
G. Sava
Utane Sawangwit
Michaela Schever
Cédric Schwab
Konstantin Schweizer
Alexandr Selyunin
Andrea Serafini
M. Settimo
Junyu Shao
V. Sharov
Hangyu Shi
Hexi Shi
Jingyang Shi
Yanan Shi
Vitaly Shutov
Andrey Sidorenkov
Fedor Šimkovic
Apeksha Singhal
Chiara Sirignano
Jaruchit Siripak
Monica Sisti
Oleg Smirnov
Sergey Sokolov
Julanan Songwadhana
Boonrucksar Soonthornthum
Albert Sotnikov
Warintorn Sreethawong
Achim Stahl
Luca Stanco
E. S. Farilla
Konstantin Stankevich
Hans Steiger
Jochen Steinmann
Tobias Sterr
Virginia Strati
Mikhail Strizh
Alexander Studenikin
Aoqi Su
Jun Su
Guangbao Sun
Mingxia Sun
Shifeng Sun
Xilei Sun
Yongzhao Sun
Zhengyang Sun
Narumon Suwonjandee
Akira Takenaka
Xiaohan Tan
Jian Tang
Jingzhe Tang
Qiang Tang
Quan Tang
Xiaodong Tang
Vidhya Thara Hariharan
Yuxin Tian
Igor Tkachev
Tomas Tmej
M. Torri
Andrea Triossi
Wladyslaw Trzaska
Yu-Chen Tung
Cristina Tuve
Nikita Ushakov
Carlo Venettacci
Giuseppe Verde
Maxim Vialkov
Benoit Viaud
Cornelius Moritz Vollbrecht
Vit Vorobel
Dmitriy Voronin
Lucia Votano
Caishen Wang
Chung-Hsiang Wang
En Wang
Han-Yang Wang
Jiabin Wang
Jun Wang
Li Wang
Meng Wang
Mingyuan Wang
Qianchuan Wang
Ruiguang Wang
Sibo Wang
Tianhong Wang
Wei Wang
Wenshuai Wang
Xi Wang
Yangfu Wang
Yaoguang Wang
Yi Wang
Yifang Wang
Yuan Wang
Yuyi Wang
Zhe Wang
Zheng Wang
Zhimin Wang
Apimook Watcharangkool
Wei Wei
Yadong Wei
Yuehuan Wei
Zhengbao Wei
Kaile Wen
Jun Weng
Christopher Wiebusch
Rosmarie Wirth
Bi Wu
Chengxin Wu
Diru Wu
Qun Wu
2025-03-02
ArXiv (prépublication)
arxiv.org
arxiv.org