Results 41 to 50 of about 4,228,228 (319)

Sparse Sequence-to-Sequence Models [PDF]

open access: yesProceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019
Sequence-to-sequence models are a powerful workhorse of NLP. Most variants employ a softmax transformation in both their attention mechanism and output layer, leading to dense alignments and strictly positive output probabilities. This density is wasteful, making models less interpretable and assigning probability mass to many implausible outputs.
Ben Peters   +2 more
openaire   +2 more sources

Quantification of within-sample genetic heterogeneity from SNP-array data

open access: yesScientific Reports, 2017
Intra-tumour genetic heterogeneity (ITH) fosters drug resistance and is a critical hurdle to clinical treatment. ITH can be well-measured using multi-region sampling but this is costly and challenging to implement.
Pierre Martinez   +5 more
doaj   +1 more source

Variational-Like Inequality Problem Involving Generalized Cayley Operator

open access: yesAxioms, 2021
This article deals with the study of a variational-like inequality problem which involves the generalized Cayley operator. We compare our problem with a fixed point equation, and based on it we construct an iterative algorithm to obtain the solution of ...
Zahoor Ahmad Rather   +2 more
doaj   +1 more source

On the property of the Smarandache-Riemann zeta sequence [PDF]

open access: yes, 2008
In this paper, some elementary methods are used to study the property of the Smarandache-Riemann zeta sequence and obtain a general ...
Yanrong, Xue
core   +1 more source

Comparison of Arachis monticola with Diploid and Cultivated Tetraploid Genomes Reveals Asymmetric Subgenome Evolution and Improvement of Peanut

open access: yesAdvanced Science, 2020
Like many important crops, peanut is a polyploid that underwent polyploidization, evolution, and domestication. The wild allotetraploid peanut species Arachis monticola (A.
Dongmei Yin   +27 more
doaj   +1 more source

First Case of a COVID-19 Patient Infected by Delta AY.4 with a Rare Deletion Leading to a N Gene Target Failure by a Specific Real Time PCR Assay: Novel Omicron VOC Might Be Doing Similar Scenario?

open access: yesMicroorganisms, 2022
Herein, we report a case of an Italian male infected by Delta sublineage AY.4 harboring an atypical deletion, leading to a N gene target failure (NGTF) by a commercial molecular assay for SARS-CoV-2 diagnosis (AllplexTM SARS-CoV-2 Assay, Seegene).
Mohammad Alkhatib   +10 more
doaj   +1 more source

European Standard Clinical Practice Guideline and EXPeRT Recommendations for the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms in Children and Adolescents

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen   +23 more
wiley   +1 more source

Tidying up international nucleotide sequence databases [PDF]

open access: yes, 2011
Sequence analysis of the ribosomal RNA operon, particularly the internal transcribed spacer (ITS) region, provides a powerful tool for identification of mycorrhizal fungi.
Schüssler, Arthur   +12 more
core   +1 more source

Deep Sequencing of FLT3‐ITD Enables Response Evaluation and Post‐Treatment Monitoring in Childhood AML: An Exploratory Study

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background An internal tandem duplication in the gene encoding Fms‐like tyrosine kinase 3 (FLT3‐ITD) is associated with high relapse risk and poor prognosis in acute myeloid leukemia (AML) and plays a crucial role in treatment decisions. Measurable residual disease (MRD) analysis of FLT3‐ITD during and after treatment has shown prognostic ...
Sofie Johansson Alm   +11 more
wiley   +1 more source

Convolutional Sequence to Sequence Learning

open access: yesCoRR, 2017
The prevalent approach to sequence to sequence learning maps an input sequence to a variable length output sequence via recurrent neural networks. We introduce an architecture based entirely on convolutional neural networks. Compared to recurrent models, computations over all elements can be fully parallelized during training and optimization is easier
Jonas Gehring   +4 more
openaire   +3 more sources

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