Deployable Reinforcement Learning with Variable Control Rate
Dong Wang
Giovanni Beltrame
2024-01-17
ArXiv (prépublication)
doi.org
arxiv.org
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
Burak Kocak
Tugba Akinci D’Antonoli
Nathaniel Mercaldo
Angel Alberich-Bayarri
Bettina Baessler
Ilaria Ambrosini
Anna E. Andreychenko
Spyridon Bakas
Regina G. H. Beets-Tan
Keno Bressem
Irene Buvat
Roberto Cannella
Luca Alessandro Cappellini
Armando Ugo Cavallo
Leonid L. Chepelev
Linda Chi Hang Chu
Aydin Demircioglu
Nandita M. deSouza
Matthias Dietzel
Salvatore Claudio Fanni … (voir 40 de plus)
Andrey Fedorov
Laure S. Fournier
Valentina Giannini
Rossano Girometti
Kevin B. W. Groot Lipman
Georgios Kalarakis
Brendan S. Kelly
Michail E. Klontzas
Dow-Mu Koh
Elmar Kotter
Ho Yun Lee
Mario Maas
Luis Marti-Bonmati
Henning Müller
Nancy Obuchowski
Fanny Orlhac
Nikolaos Papanikolaou
Ekaterina Petrash
Elisabeth Pfaehler
Daniel Pinto dos Santos
Andrea Ponsiglione
Sebastià Sabater
Francesco Sardanelli
Philipp Seeböck
Nanna M. Sijtsema
Arnaldo Stanzione
Alberto Traverso
Lorenzo Ugga
Martin Vallières
Lisanne V. van Dijk
Joost J. M. van Griethuysen
Robbert W. van Hamersvelt
Peter van Ooijen
Federica Vernuccio
Alan Wang
Stuart Williams
Jan Witowski
Zhongyi Zhang
Alex Zwanenburg
Renato Cuocolo
2024-01-17
Insights into Imaging (publié)
doi.org
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
Burak Kocak
Tugba Akinci D’Antonoli
Nathaniel Mercaldo
Angel Alberich-Bayarri
Bettina Baessler
Ilaria Ambrosini
Anna E. Andreychenko
Spyridon Bakas
Regina G. H. Beets-Tan
Keno Bressem
Irene Buvat
Roberto Cannella
Luca Alessandro Cappellini
Armando Ugo Cavallo
Leonid L. Chepelev
Linda Chi Hang Chu
Aydin Demircioglu
Nandita M. deSouza
Matthias Dietzel
Salvatore Claudio Fanni … (voir 40 de plus)
Andrey Fedorov
Laure S. Fournier
Valentina Giannini
Rossano Girometti
Kevin B. W. Groot Lipman
Georgios Kalarakis
Brendan S. Kelly
Michail E. Klontzas
Dow-Mu Koh
Elmar Kotter
Ho Yun Lee
Mario Maas
Luis Marti-Bonmati
Henning Müller
Nancy Obuchowski
Fanny Orlhac
Nikolaos Papanikolaou
Ekaterina Petrash
Elisabeth Pfaehler
Daniel Pinto dos Santos
Andrea Ponsiglione
Sebastià Sabater
Francesco Sardanelli
Philipp Seeböck
Nanna M. Sijtsema
Arnaldo Stanzione
Alberto Traverso
Lorenzo Ugga
Martin Vallières
Lisanne V. van Dijk
Joost J. M. van Griethuysen
Robbert W. van Hamersvelt
Peter van Ooijen
Federica Vernuccio
Alan Wang
Stuart Williams
Jan Witowski
Zhongyi Zhang
Alex Zwanenburg
Renato Cuocolo
2024-01-17
Insights into Imaging (publié)
doi.org
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
Burak Kocak
Tugba Akinci D’Antonoli
Nathaniel Mercaldo
Angel Alberich-Bayarri
Bettina Baessler
Ilaria Ambrosini
Anna E. Andreychenko
Spyridon Bakas
Regina G. H. Beets-Tan
Keno Bressem
Irene Buvat
Roberto Cannella
Luca Alessandro Cappellini
Armando Ugo Cavallo
Leonid L. Chepelev
Linda Chi Hang Chu
Aydin Demircioglu
Nandita M. deSouza
Matthias Dietzel
Salvatore Claudio Fanni … (voir 40 de plus)
Andrey Fedorov
Laure S. Fournier
Valentina Giannini
Rossano Girometti
Kevin B. W. Groot Lipman
Georgios Kalarakis
Brendan S. Kelly
Michail E. Klontzas
Dow-Mu Koh
Elmar Kotter
Ho Yun Lee
Mario Maas
Luis Marti-Bonmati
Henning Müller
Nancy Obuchowski
Fanny Orlhac
Nikolaos Papanikolaou
Ekaterina Petrash
Elisabeth Pfaehler
Daniel Pinto dos Santos
Andrea Ponsiglione
Sebastià Sabater
Francesco Sardanelli
Philipp Seeböck
Nanna M. Sijtsema
Arnaldo Stanzione
Alberto Traverso
Lorenzo Ugga
Martin Vallières
Lisanne V. van Dijk
Joost J. M. van Griethuysen
Robbert W. van Hamersvelt
Peter van Ooijen
Federica Vernuccio
Alan Wang
Stuart Williams
Jan Witowski
Zhongyi Zhang
Alex Zwanenburg
Renato Cuocolo
2024-01-17
Insights into Imaging (publié)
doi.org
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
Burak Kocak
Tugba Akinci D’Antonoli
Nathaniel Mercaldo
Angel Alberich-Bayarri
Bettina Baessler
Ilaria Ambrosini
Anna E. Andreychenko
Spyridon Bakas
Regina G. H. Beets-Tan
Keno Bressem
Irene Buvat
Roberto Cannella
Luca Alessandro Cappellini
Armando Ugo Cavallo
Leonid L. Chepelev
Linda Chi Hang Chu
Aydin Demircioglu
Nandita M. deSouza
Matthias Dietzel
Salvatore Claudio Fanni … (voir 40 de plus)
Andrey Fedorov
Laure S. Fournier
Valentina Giannini
Rossano Girometti
Kevin B. W. Groot Lipman
Georgios Kalarakis
Brendan S. Kelly
Michail E. Klontzas
Dow-Mu Koh
Elmar Kotter
Ho Yun Lee
Mario Maas
Luis Marti-Bonmati
Henning Müller
Nancy Obuchowski
Fanny Orlhac
Nikolaos Papanikolaou
Ekaterina Petrash
Elisabeth Pfaehler
Daniel Pinto dos Santos
Andrea Ponsiglione
Sebastià Sabater
Francesco Sardanelli
Philipp Seeböck
Nanna M. Sijtsema
Arnaldo Stanzione
Alberto Traverso
Lorenzo Ugga
Martin Vallières
Lisanne V. van Dijk
Joost J. M. van Griethuysen
Robbert W. van Hamersvelt
Peter van Ooijen
Federica Vernuccio
Alan Wang
Stuart Williams
Jan Witowski
Zhongyi Zhang
Alex Zwanenburg
Renato Cuocolo
2024-01-17
Insights into Imaging (publié)
doi.org
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
Burak Kocak
Tugba Akinci D’Antonoli
Nathaniel Mercaldo
Angel Alberich-Bayarri
Bettina Baessler
Ilaria Ambrosini
Anna E. Andreychenko
Spyridon Bakas
Regina G. H. Beets-Tan
Keno Bressem
Irene Buvat
Roberto Cannella
Luca Alessandro Cappellini
Armando Ugo Cavallo
Leonid L. Chepelev
Linda Chi Hang Chu
Aydin Demircioglu
Nandita M. deSouza
Matthias Dietzel
Salvatore Claudio Fanni … (voir 40 de plus)
Andrey Fedorov
Laure S. Fournier
Valentina Giannini
Rossano Girometti
Kevin B. W. Groot Lipman
Georgios Kalarakis
Brendan S. Kelly
Michail E. Klontzas
Dow-Mu Koh
Elmar Kotter
Ho Yun Lee
Mario Maas
Luis Marti-Bonmati
Henning Müller
Nancy Obuchowski
Fanny Orlhac
Nikolaos Papanikolaou
Ekaterina Petrash
Elisabeth Pfaehler
Daniel Pinto dos Santos
Andrea Ponsiglione
Sebastià Sabater
Francesco Sardanelli
Philipp Seeböck
Nanna M. Sijtsema
Arnaldo Stanzione
Alberto Traverso
Lorenzo Ugga
Martin Vallières
Lisanne V. van Dijk
Joost J. M. van Griethuysen
Robbert W. van Hamersvelt
Peter van Ooijen
Federica Vernuccio
Alan Wang
Stuart Williams
Jan Witowski
Zhongyi Zhang
Alex Zwanenburg
Renato Cuocolo
2024-01-17
Insights into Imaging (publié)
doi.org
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
Burak Kocak
Tugba Akinci D’Antonoli
Nathaniel Mercaldo
Angel Alberich-Bayarri
Bettina Baessler
Ilaria Ambrosini
Anna E. Andreychenko
Spyridon Bakas
Regina G. H. Beets-Tan
Keno Bressem
Irene Buvat
Roberto Cannella
Luca Alessandro Cappellini
Armando Ugo Cavallo
Leonid L. Chepelev
Linda Chi Hang Chu
Aydin Demircioglu
Nandita M. deSouza
Matthias Dietzel
Salvatore Claudio Fanni … (voir 40 de plus)
Andrey Fedorov
Laure S. Fournier
Valentina Giannini
Rossano Girometti
Kevin B. W. Groot Lipman
Georgios Kalarakis
Brendan S. Kelly
Michail E. Klontzas
Dow-Mu Koh
Elmar Kotter
Ho Yun Lee
Mario Maas
Luis Marti-Bonmati
Henning Müller
Nancy Obuchowski
Fanny Orlhac
Nikolaos Papanikolaou
Ekaterina Petrash
Elisabeth Pfaehler
Daniel Pinto dos Santos
Andrea Ponsiglione
Sebastià Sabater
Francesco Sardanelli
Philipp Seeböck
Nanna M. Sijtsema
Arnaldo Stanzione
Alberto Traverso
Lorenzo Ugga
Martin Vallières
Lisanne V. van Dijk
Joost J. M. van Griethuysen
Robbert W. van Hamersvelt
Peter van Ooijen
Federica Vernuccio
Alan Wang
Stuart Williams
Jan Witowski
Zhongyi Zhang
Alex Zwanenburg
Renato Cuocolo
2024-01-17
Insights into Imaging (publié)
doi.org
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
Burak Kocak
Tugba Akinci D’Antonoli
Nathaniel Mercaldo
Angel Alberich-Bayarri
Bettina Baessler
Ilaria Ambrosini
Anna E. Andreychenko
Spyridon Bakas
Regina G. H. Beets-Tan
Keno Bressem
Irene Buvat
Roberto Cannella
Luca Alessandro Cappellini
Armando Ugo Cavallo
Leonid L. Chepelev
Linda Chi Hang Chu
Aydin Demircioglu
Nandita M. deSouza
Matthias Dietzel
Salvatore Claudio Fanni … (voir 40 de plus)
Andrey Fedorov
Laure S. Fournier
Valentina Giannini
Rossano Girometti
Kevin B. W. Groot Lipman
Georgios Kalarakis
Brendan S. Kelly
Michail E. Klontzas
Dow-Mu Koh
Elmar Kotter
Ho Yun Lee
Mario Maas
Luis Marti-Bonmati
Henning Müller
Nancy Obuchowski
Fanny Orlhac
Nikolaos Papanikolaou
Ekaterina Petrash
Elisabeth Pfaehler
Daniel Pinto dos Santos
Andrea Ponsiglione
Sebastià Sabater
Francesco Sardanelli
Philipp Seeböck
Nanna M. Sijtsema
Arnaldo Stanzione
Alberto Traverso
Lorenzo Ugga
Martin Vallières
Lisanne V. van Dijk
Joost J. M. van Griethuysen
Robbert W. van Hamersvelt
Peter van Ooijen
Federica Vernuccio
Alan Wang
Stuart Williams
Jan Witowski
Zhongyi Zhang
Alex Zwanenburg
Renato Cuocolo
2024-01-17
Insights into Imaging (publié)
doi.org
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
Burak Kocak
Tugba Akinci D’Antonoli
Nathaniel Mercaldo
Angel Alberich-Bayarri
Bettina Baessler
Ilaria Ambrosini
Anna E. Andreychenko
Spyridon Bakas
Regina G. H. Beets-Tan
Keno Bressem
Irene Buvat
Roberto Cannella
Luca Alessandro Cappellini
Armando Ugo Cavallo
Leonid L. Chepelev
Linda Chi Hang Chu
Aydin Demircioglu
Nandita M. deSouza
Matthias Dietzel
Salvatore Claudio Fanni … (voir 40 de plus)
Andrey Fedorov
Laure S. Fournier
Valentina Giannini
Rossano Girometti
Kevin B. W. Groot Lipman
Georgios Kalarakis
Brendan S. Kelly
Michail E. Klontzas
Dow-Mu Koh
Elmar Kotter
Ho Yun Lee
Mario Maas
Luis Marti-Bonmati
Henning Müller
Nancy Obuchowski
Fanny Orlhac
Nikolaos Papanikolaou
Ekaterina Petrash
Elisabeth Pfaehler
Daniel Pinto dos Santos
Andrea Ponsiglione
Sebastià Sabater
Francesco Sardanelli
Philipp Seeböck
Nanna M. Sijtsema
Arnaldo Stanzione
Alberto Traverso
Lorenzo Ugga
Martin Vallières
Lisanne V. van Dijk
Joost J. M. van Griethuysen
Robbert W. van Hamersvelt
Peter van Ooijen
Federica Vernuccio
Alan Wang
Stuart Williams
Jan Witowski
Zhongyi Zhang
Alex Zwanenburg
Renato Cuocolo
2024-01-17
Insights into Imaging (publié)
doi.org
Abstract B049: Pancreatic beta cell stress pathways drive pancreatic ductal adenocarcinoma development in obesity
Cathy C. Garcia
Aarthi Venkat
Alex Tong
Sherry Agabiti
Lauren Lawres
Rebecca Cardone
Richard G. Kibbey
Smita Krishnaswamy
Mandar Deepak Muzumdar
2024-01-16
Cancer Research (publié)
doi.org
Amortizing intractable inference in large language models
Edward J Hu
Moksh J. Jain
Eric Elmoznino
Younesse Kaddar
Guillaume Lajoie
Yoshua Bengio
Nikolay Malkin
Autoregressive large language models (LLMs) compress knowledge from their training data through next-token conditional distributions. This l… (voir plus)imits tractable querying of this knowledge to start-to-end autoregressive sampling. However, many tasks of interest -- including sequence continuation, infilling, and other forms of constrained generation -- involve sampling from intractable posterior distributions. We address this limitation by using amortized Bayesian inference to sample from these intractable posteriors. Such amortization is algorithmically achieved by fine-tuning LLMs via diversity-seeking reinforcement learning algorithms: generative flow networks (GFlowNets). We empirically demonstrate that this distribution-matching paradigm of LLM fine-tuning can serve as an effective alternative to maximum-likelihood training and reward-maximizing policy optimization. As an important application, we interpret chain-of-thought reasoning as a latent variable modeling problem and demonstrate that our approach enables data-efficient adaptation of LLMs to tasks that require multi-step rationalization and tool use.
2024-01-16
ICLR.cc/2024/Conference (présentation orale)
doi.org
openreview.net
Balancing Act: Constraining Disparate Impact in Sparse Models
Meraj Hashemizadeh
Juan Ramirez
Rohan Sukumaran
Golnoosh Farnadi
Simon Lacoste-Julien
Jose Gallego-Posada
Model pruning is a popular approach to enable the deployment of large deep learning models on edge devices with restricted computational or … (voir plus)storage capacities. Although sparse models achieve performance comparable to that of their dense counterparts at the level of the entire dataset, they exhibit high accuracy drops for some data sub-groups. Existing methods to mitigate this disparate impact induced by pruning (i) rely on surrogate metrics that address the problem indirectly and have limited interpretability; or (ii) scale poorly with the number of protected sub-groups in terms of computational cost. We propose a constrained optimization approach that directly addresses the disparate impact of pruning: our formulation bounds the accuracy change between the dense and sparse models, for each sub-group. This choice of constraints provides an interpretable success criterion to determine if a pruned model achieves acceptable disparity levels. Experimental results demonstrate that our technique scales reliably to problems involving large models and hundreds of protected sub-groups.
2024-01-16
ICLR.cc/2024/Conference (poster)
doi.org
openreview.net