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
DialEgg: Dialect-Agnostic MLIR Optimizer using Equality Saturation with Egglog
Abd-El-Aziz Zayed
Christophe Dubach
MLIR’s ability to optimize programs at multiple levels of abstraction is key to enabling domain-specific optimizing compilers. However, ex… (voir plus)pressing optimizations remains tedious. Optimizations can interact in unexpected ways, making it hard to unleash full performance. Equality saturation promises to solve these challenges. First, it simplifies the expression of optimizations using rewrite rules. Secondly, it considers all possible optimization interactions, through saturation, selecting the best program variant. Despite these advantages, equality saturation remains absent from production compilers such as MLIR. This paper proposes to integrate Egglog, a recent equality saturation engine, with MLIR, in a dialect-agnostic manner. This paper shows how the main MLIR constructs such as operations, types or attributes can be modeled in Egglog. It also presents DialEgg, a tool that pre-defines a large set of common MLIR constructs in Egglog and automatically translates between the MLIR and Egglog program representations. This paper uses a few use cases to demonstrate the potential for combining equality saturation and MLIR.
2025-03-01
IEEE/ACM International Symposium on Code Generation and Optimization (publié)
doi.org
Ensemble machine learning to accelerate industrial decarbonization: Prediction of Hansen solubility parameters for streamlined chemical solvent selection
Eslam G. Al-Sakkari
Ahmed Ragab
Mostafa Amer
Olumoye Ajao
Marzouk Benali
Daria C. Boffito
Hanane Dagdougui
Mouloud Amazouz
2025-03-01
Digital Chemical Engineering (publié)
doi.org
Implicit Generative Modeling by Kernel Similarity Matching
Shubham Choudhary
Paul Masset
Demba Ba
2025-03-01
ArXiv (prépublication)
arxiv.org
arxiv.org
Implicit Generative Modeling by Kernel Similarity Matching
Shubham Choudhary
Paul Masset
Demba Ba
Understanding how the brain encodes stimuli has been a fundamental problem in computational neuroscience. Insights into this problem have le… (voir plus)d to the design and development of artificial neural networks that learn representations by incorporating brain-like learning abilities. Recently, learning representations by capturing similarity between input samples has been studied to tackle this problem. This approach, however, has thus far been used to only learn downstream features from an input and has not been studied in the context of a generative paradigm, where one can map the representations back to the input space, incorporating not only bottom-up interactions (stimuli to latent) but also learning features in a top-down manner (latent to stimuli). We investigate a kernel similarity matching framework for generative modeling. Starting with a modified sparse coding objective for learning representations proposed in prior work, we demonstrate that representation learning in this context is equivalent to maximizing similarity between the input kernel and a latent kernel. We show that an implicit generative model arises from learning the kernel structure in the latent space and show how the framework can be adapted to learn manifold structures, potentially providing insights as to how task representations can be encoded in the brain. To solve the objective, we propose a novel Alternate Direction Method of Multipliers (ADMM) based algorithm and discuss the interpretation of the optimization process. Finally, we discuss how this representation learning problem can lead towards a biologically plausible architecture to learn the model parameters that ties together representation learning using similarity matching (a bottom-up approach) with predictive coding (a top-down approach).
2025-03-01
ArXiv (prépublication)
arxiv.org
arxiv.org
Improving clustering quality evaluation in noisy Gaussian mixtures
Renato Cordeiro De Amorim
Vladimir Makarenkov
2025-03-01
ArXiv (prépublication)
arxiv.org
arxiv.org
Improving internal cluster quality evaluation in noisy Gaussian mixtures
Renato Cordeiro De Amorim
Vladimir Makarenkov
Clustering is a fundamental technique in machine learning and data analysis, widely used across various domains. Internal clustering validat… (voir plus)ion measures, such as the Average Silhouette Width, Calinski-Harabasz, and Davies-Bouldin indices, play a crucial role in assessing clustering quality when external ground truth labels are unavailable. However, these measures can be affected by feature relevance, potentially leading to unreliable evaluations in high-dimensional or noisy data sets. In this paper, we introduce a Feature Importance Rescaling (FIR) method designed to enhance internal clustering validation by adjusting feature contributions based on their dispersion. Our method systematically attenuates noise features making clustering compactness and separation clearer, and by consequence aligning internal validation measures more closely with the ground truth. Through extensive experiments on synthetic data sets under different configurations, we demonstrate that FIR consistently improves the correlation between internal validation indices and the ground truth, particularly in settings with noisy or irrelevant features. The results show that FIR increases the robustness of clustering evaluation, reduces variability in performance across different data sets, and remains effective even when clusters exhibit significant overlap. These findings highlight the potential of FIR as a valuable enhancement for internal clustering validation, making it a practical tool for unsupervised learning tasks where labelled data is not available.
2025-03-01
ArXiv (prépublication)
arxiv.org
arxiv.org
Improving internal cluster quality evaluation in noisy Gaussian mixtures
Renato Cordeiro De Amorim
Vladimir Makarenkov
Clustering is a fundamental technique in machine learning and data analysis, widely used across various domains. Internal clustering validat… (voir plus)ion measures, such as the Average Silhouette Width, Calinski-Harabasz, and Davies-Bouldin indices, play a crucial role in assessing clustering quality when external ground truth labels are unavailable. However, these measures can be affected by feature relevance, potentially leading to unreliable evaluations in high-dimensional or noisy data sets. In this paper, we introduce a Feature Importance Rescaling (FIR) method designed to enhance internal clustering validation by adjusting feature contributions based on their dispersion. Our method systematically attenuates noise features making clustering compactness and separation clearer, and by consequence aligning internal validation measures more closely with the ground truth. Through extensive experiments on synthetic data sets under different configurations, we demonstrate that FIR consistently improves the correlation between internal validation indices and the ground truth, particularly in settings with noisy or irrelevant features. The results show that FIR increases the robustness of clustering evaluation, reduces variability in performance across different data sets, and remains effective even when clusters exhibit significant overlap. These findings highlight the potential of FIR as a valuable enhancement for internal clustering validation, making it a practical tool for unsupervised learning tasks where labelled data is not available.
2025-03-01
ArXiv (prépublication)
arxiv.org
arxiv.org
Interpretable deep learning for deconvolutional analysis of neural signals
Bahareh Tolooshams
Sara Matias
Hao Wu
Simona Temereanca
Naoshige Uchida
Venkatesh N. Murthy
Paul Masset
Demba Ba
2025-03-01
Neuron (publié)
doi.org
Large language models deconstruct the clinical intuition behind diagnosing autism
Jack Stanley
Emmett Rabot
Siva Reddy
Eugene Belilovsky
L. Mottron
Danilo Bzdok
2025-03-01
Cell (publié)
doi.org