Publications

Learning Lyapunov-Stable Polynomial Dynamical Systems Through Imitation
Amin Abyaneh
Hsiu-Chin Lin
Imitation learning is a paradigm to address complex motion planning problems by learning a policy to imitate an expert’s behavior. However… (voir plus), relying solely on the expert’s data might lead to unsafe actions when the robot deviates from the demonstrated trajectories. Stability guarantees have previously been provided utilizing nonlinear dynamical systems, acting as high-level motion planners, in conjunction with the Lyapunov stability theorem. Yet, these methods are prone to inaccurate policies, high computational cost, sample inefficiency, or quasi stability when replicating complex and highly nonlinear trajectories. To mitigate this problem, we present an approach for learning a globally stable nonlinear dynamical system as a motion planning policy. We model the nonlinear dynamical system as a parametric polynomial and learn the polynomial’s coefficients jointly with a Lyapunov candidate. To showcase its success, we compare our method against the state of the art in simulation and conduct real-world experiments with the Kinova Gen3 Lite manipulator arm. Our experiments demonstrate the sample efficiency and reproduction accuracy of our method for various expert trajectories, while remaining stable in the face of perturbations.
2023-12-02
Proceedings of The 7th Conference on Robot Learning (publié)
doi.org
openreview.net
Advancing Clinical Psychiatry: Integration of Clinical and Omics Data Using Machine Learning
Bill Qi
Yannis Trakadis
2023-12-01
Biological Psychiatry (publié)
doi.org
Automatic Head and Neck Tumor segmentation and outcome prediction relying on FDG-PET/CT images: Findings from the second edition of the HECKTOR challenge
Vincent Andrearczyk
Valentin Oreiller
Sarah Boughdad
Catherine Cheze Le Rest
Olena Tankyevych
Hesham M. Elhalawani
Mario Jreige
John O. Prior
Martin Vallières
Dimitris Visvikis
Mathieu Hatt
Adrien Depeursinge
2023-12-01
Medical Image Analysis (publié)
doi.org
Balaur: Language Model Pretraining with Lexical Semantic Relations
Andrei Mircea
Jackie Cheung
2023-12-01
Findings of the Association for Computational Linguistics: EMNLP 2023 (publié)
doi.org
openreview.net
Brain decoding of the Human Connectome Project tasks in a dense individual fMRI dataset
Shima Rastegarnia
Marie St-Laurent
Elizabeth DuPre
Basile Pinsard
Pierre (Louis) Bellec
2023-12-01
NeuroImage (publié)
doi.org
Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model
Parishad BehnamGhader
Santiago Miret
Siva Reddy
Augmenting pretrained language models with retrievers to select the supporting documents has shown promise in effectively solving common NLP… (voir plus) problems, including language modeling and question answering, in an interpretable way. In this paper, we first study the strengths and weaknesses of different retriever-augmented language models (REALM,
2023-12-01
Findings of the Association for Computational Linguistics: EMNLP 2023 (publié)
doi.org
openreview.net
Cross-lingual Open-Retrieval Question Answering for African Languages
Odunayo Ogundepo
Tajuddeen Gwadabe
Clara E. Rivera
Jonathan H. Clark
Sebastian Ruder
David Ifeoluwa Adelani
Bonaventure F. P. Dossou
Abdou Aziz DIOP
Claytone Sikasote
Gilles Q. Hacheme
Happy Buzaaba
Ignatius Majesty Ezeani
Rooweither Mabuya
Salomey Osei
Chris Emezue
Albert Njoroge Kahira
Shamsuddeen Hassan Muhammad
Akintunde Oladipo
Abraham Toluwase Owodunni
Atnafu Lambebo Tonja … (voir 24 de plus)
Iyanuoluwa Shode
Akari Asai
Aremu Anuoluwapo
Ayodele Awokoya
Bernard Opoku
Chiamaka Ijeoma Chukwuneke
Christine Mwase
Clemencia Siro
Stephen Arthur
Tunde Oluwaseyi Ajayi
V. Otiende
Andre Niyongabo Rubungo
B. Sinkala
Daniel A. Ajisafe
Emeka Onwuegbuzia
Falalu Lawan
Ibrahim Ahmad
Jesujoba Alabi
CHINEDU EMMANUEL MBONU
Mofetoluwa Adeyemi
Mofya Phiri
Orevaoghene Ahia
Ruqayya Nasir Iro
Sonia Adhiambo
2023-12-01
Findings of the Association for Computational Linguistics: EMNLP 2023 (publié)
doi.org
Cross-lingual Open-Retrieval Question Answering for African Languages
Odunayo Ogundepo
Tajuddeen Gwadabe
Clara E. Rivera
Jonathan H. Clark
Sebastian Ruder
David Ifeoluwa Adelani
Bonaventure F. P. Dossou
Abdou Aziz DIOP
Claytone Sikasote
Gilles HACHEME
Happy Buzaaba
Ignatius Ezeani
Rooweither Mabuya
Salomey Osei
Chris Emezue
Albert Kahira
Shamsuddeen Hassan Muhammad
Akintunde Oladipo
Abraham Toluwase Owodunni
Atnafu Lambebo Tonja … (voir 32 de plus)
Iyanuoluwa Shode
Akari Asai
Tunde Oluwaseyi Ajayi
Clemencia Siro
Stephen Arthur
Mofetoluwa Adeyemi
Orevaoghene Ahia
Aremu Anuoluwapo
Oyinkansola Awosan
Chiamaka Ijeoma Chukwuneke
Bernard Opoku
Ayodele Awokoya
Verrah Akinyi Otiende
Christine Mwase
Boyd Sinkala
Andre Niyongabo Rubungo
Daniel Ajisafe
Emeka Felix Onwuegbuzia
Habib Mbow
Emile Niyomutabazi
Eunice Mukonde
Falalu Lawan
Ibrahim Ahmad
Jesujoba Oluwadara Alabi
Martin Namukombo
CHINEDU EMMANUEL MBONU
Mofya Phiri
Neo Putini
Ndumiso Mngoma
Priscilla A. Amuok
Ruqayya Nasir Iro
Sonia Adhiambo
2023-12-01
Findings of the Association for Computational Linguistics: EMNLP 2023 (publié)
doi.org
openreview.net
Current AI applications in neurology: Brain imaging
Tal Arbel
Joshua D. Durso-Finley
Jean-Pierre R. Falet
Raghav Mehta
Douglas Arnold
Nick Pawlowski
2023-12-01
Journal of the Neurological Sciences (publié)
doi.org
A framework for fair decision-making over time with time-invariant utilities
Andrea Lodi
Sriram Sankaranarayanan
Guanyi Wang
2023-12-01
European Journal of Operational Research (publié)
doi.org
arxiv.org
From physics to sentience: Deciphering the semantics of the free-energy principle and evaluating its claims: Comment on "Path integrals, particular kinds, and strange things" by Karl Friston et al.
Zahra Sheikhbahaee
Adam Safron
Casper Hesp
Guillaume Dumas
2023-12-01
Physics of Life Reviews (publié)
doi.org
arxiv.org
Large language models: What could they do for neurology?
Guillaume Lajoie
2023-12-01
Journal of the Neurological Sciences (publié)
doi.org