Publications

Step-GRAND: A Low Latency Universal Soft-Input Decoder
Syed Mohsin Abbas
Marwan Jalaleddine
Chi-Ying Tsui
Warren J. Gross
GRAND features both soft-input and hard-input variants that are well suited to efficient hardware implementations that can be characterized … (see more)with achievable average and worst-case decoding latency. This paper introduces step-GRAND, a soft-input variant of GRAND that, in addition to achieving appealing average decoding latency, also reduces the worst-case decoding latency of the corresponding hardware implementation. The hardware implementation results demonstrate that the proposed step-GRAND can decode CA-polar code (128,105+11) with an average information throughput of 47.7 Gbps at the target FER of
Decision Diagrams in Space!
Isaac Rudich
Manuel L'opez-Ib'anez
Michael Romer
Louis-Martin Rousseau
Advancing Clinical Psychiatry: Integration of Clinical and Omics Data Using Machine Learning
Bill Qi
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
Dimitris Visvikis
Mathieu Hatt
Adrien Depeursinge
Balaur: Language Model Pretraining with Lexical Semantic Relations
Jackie CK Cheung
Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model
Augmenting pretrained language models with retrievers to select the supporting documents has shown promise in effectively solving common NLP… (see more) 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,
Current AI applications in neurology: Brain imaging
Joshua D. Durso-Finley
Jean-Pierre R. Falet
Raghav Mehta
Douglas Arnold
Nick Pawlowski
DiPS: Discriminative Pseudo-Label Sampling with Self-Supervised Transformers for Weakly Supervised Object Localization
Shakeeb Murtaza
Soufiane Belharbi
Aydin Sarraf
Eric Granger
Dissociable influences of maternal vs paternal Alzheimer’s risk on neurocognitive and cardiovascular health in men and women
Frederic St‐Onge
Sylvia Villeneuve
AmanPreet Badhwar
Sarah A Gagliano Taliun
Sali Farhan
Maiya R. Geddes
Yasser Iturria Medina
Judes Poirier
R. Nathan Spreng
We uncovered IPs of AD susceptibility differently expressed in male and female probands and affected by the diagnosed parent’s sex. Matern… (see more)al inheritance highlighted memory performance in both sexes, whereas paternal inheritance was particularly linked to cardiovascular health in males. The inheritance of the IPs was reflected in the brain structure at both superficial and deeper layers of the cortex. As the first study of its kind, our cross‐generational analysis of matri‐ vs. patrilinear AD risk bridges the epidemiological and clinical literature by leveraging the power of ∼1,000 patient visits. Our completely data‐driven framework ultimately dissociated phenotypes of maternal and paternal AD risk single‐handedly expressed in male and female probands.
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.
Adam Safron
Casper Hesp
Gene-metabolite annotation with shortest reactional distance enhances metabolite genome-wide association studies results
Sarah Cherkaoui
Sandra Therrien-Laperriere
Yann Ilboudo
Raphaël Poujol
Pamela Mehanna
Melanie E. Garrett
Marilyn J. Telen
Allison E. Ashley-Koch
Pablo Bartolucci
John D. Rioux
Guillaume Lettre
Christine Des Rosiers
Matthieu Ruiz
Julie G. Hussin
Studies combining metabolomics and genetics, known as metabolite genome-wide association studies (mGWAS), have provided valuable insights in… (see more)to our understanding of the genetic control of metabolite levels. However, the biological interpretation of these associations remains challenging due to a lack of existing tools to annotate mGWAS gene-metabolite pairs beyond the use of conservative statistical significance threshold. Here, we computed the shortest reactional distance (SRD) based on the curated knowledge of the KEGG database to explore its utility in enhancing the biological interpretation of results from three independent mGWAS, including a case study on sickle cell disease patients. Results show that, in reported mGWAS pairs, there is an excess of small SRD values and that SRD values and p-values significantly correlate, even beyond the standard conservative thresholds. The added-value of SRD annotation is shown for identification of potential false negative hits, exemplified by the finding of gene-metabolite associations with SRD ≤1 that did not reach standard genome-wide significance cut-off. The wider use of this statistic as an mGWAS annotation would prevent the exclusion of biologically relevant associations and can also identify errors or gaps in current metabolic pathway databases. Our findings highlight the SRD metric as an objective, quantitative and easy-to-compute annotation for gene-metabolite pairs that can be used to integrate statistical evidence to biological networks.
Growth of TiO2 single crystals by the Verneuil method at different gas flow ratio
Xudong Liu
Hanshu Ma
Wei Wang
Yongqi Hu
Xudong Sun