:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Engelmann, Justin, Moukaddem, Diana, Gago, Lucas, Strang, Niall, Bernabeu, Miguel O.
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Quantitative Methods Computer Vision and Pattern Recognition
Accesso online:	https://arxiv.org/abs/2403.06950
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Training a high-performance retinal foundation model with half-the-data and 400 times less compute
di: Engelmann, Justin, et al.
Pubblicazione: (2024)

Beware of so-called 'good' correlations: a statistical reality check on individual mRNA-protein predictions
di: Gosselin, Romain-Daniel
Pubblicazione: (2025)

DiffeoMorph: Learning to Morph 3D Shapes Using Differentiable Agent-Based Simulations
di: Pahng, Seong Ho, et al.
Pubblicazione: (2025)

Fractal Geometry and Fractional Calculus for Integrative Morphological Mapping of Breast Cancer Complexity
di: Das, Abhijeet, et al.
Pubblicazione: (2025)

Domain-specific augmentations with resolution agnostic self-attention mechanism improves choroid segmentation in optical coherence tomography images
di: Burke, Jamie, et al.
Pubblicazione: (2024)

AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein Engineering
di: Liu, Yungeng, et al.
Pubblicazione: (2024)

A Robust Nonparametric Framework for Detecting Repeated Spatial Patterns
di: Senanayake, Rajitha, et al.
Pubblicazione: (2025)

Efficient gPC-based quantification of probabilistic robustness for systems in neuroscience
di: Sutulovic, Uros, et al.
Pubblicazione: (2024)

Considering experimental frame rates and robust segmentation analysis of piecewise-linear microparticle trajectories
di: Cook, Keisha J., et al.
Pubblicazione: (2024)

Self-organized clustering, prediction, and superposition of long-term cognitive decline from short-term individual cognitive test scores in Alzheimer's disease
di: Sato, Hiroyuki, et al.
Pubblicazione: (2024)

Automated 2D and 3D Finite Element Overclosure Adjustment and Mesh Morphing Using Generalized Regression Neural Networks
di: Andreassen, Thor E., et al.
Pubblicazione: (2022)

MorphGen: Controllable and Morphologically Plausible Generative Cell-Imaging
di: Demirel, Berker, et al.
Pubblicazione: (2025)

Precision psychiatry: predicting predictability
di: van Dellen, Edwin
Pubblicazione: (2023)

Exploring the limits of pre-trained embeddings in machine-guided protein design: a case study on predicting AAV vector viability
di: Rodrigues, Ana F., et al.
Pubblicazione: (2026)

Opportunities and challenges in protein structure prediction
di: Wenkai Wang, et al.
Pubblicazione: (2026)

retinalysis-fundusprep: A python package for robust color fundus image bounds extraction
di: Quiros, Jose Vargas, et al.
Pubblicazione: (2025)

Practical and scalable simulations of non-Markovian stochastic processes and temporal networks with individual node properties
di: Pelissier, Aurelien, et al.
Pubblicazione: (2022)

Fractal Language Modelling by Universal Sequence Maps (USM)
di: Almeida, Jonas S, et al.
Pubblicazione: (2025)

Coarse-Graining Cascades Within Food Webs
di: Yeakel, Justin D.
Pubblicazione: (2025)

AI prediction of cardiovascular events using opportunistic epicardial adipose tissue assessments from CT calcium score
di: Hu, Tao, et al.
Pubblicazione: (2024)

Hyperdimensional computing: a fast, robust and interpretable paradigm for biological data
di: Stock, Michiel, et al.
Pubblicazione: (2024)

Uncertainty quantification of receptor ligand binding sites prediction
di: Chen, Nanjie, et al.
Pubblicazione: (2024)

Inferring and predicting Fried physical frailty phenotype deficits
di: Pridham, Glen, et al.
Pubblicazione: (2025)

Practical indistinguishability in a gene regulatory network inference problem, a case study
di: FitzGerald, Cody E., et al.
Pubblicazione: (2025)

Bayesian ensemble learning for predicting health outcomes of multipollutant mixtures
di: Ning, Yu-Chien, et al.
Pubblicazione: (2025)

Functional predictability of universal gene circuits in diverse microbial hosts
di: Chenrui Qin, et al.
Pubblicazione: (2024)

i-GRIP, a Grasping Movement Intention Estimator for Intuitive Control of Assistive Devices
di: Moullet, Etienne, et al.
Pubblicazione: (2024)

A Grasping Movement Intention Estimator for Intuitive Control of Assistive Devices
di: Moullet, Etienne, et al.
Pubblicazione: (2024)

Argentine ants regulate traffic flow with stopped individuals
di: Dobramysl, Ulrich, et al.
Pubblicazione: (2024)

Ising energy model for the stochastic prediction of tumor islets
di: Amoudruz, Lucas, et al.
Pubblicazione: (2025)

Automated multi-dataset INST $^{13}$C metabolic flux analysis at microliter scale reveals robust fluxes but variable metabolite pools in $Corynebacterium~glutamicum$
di: Nießer, Jochen, et al.
Pubblicazione: (2026)

Explainable artificial intelligence in breast cancer detection and risk prediction: A systematic scoping review
di: Ghasemi, Amirehsan, et al.
Pubblicazione: (2024)

INDIGENA: inductive prediction of disease-gene associations using phenotype ontologies
di: Zhapa-Camacho, Fernando, et al.
Pubblicazione: (2026)

Implementation of an AI-based MRD evaluation and prediction model for multiple myeloma
di: Chen, Jianfeng, et al.
Pubblicazione: (2024)

Physics‐informed multimodal learning for snapshot dental spectral reflectance prediction
di: Yujun Feng, et al.
Pubblicazione: (2026)

Deep learning for drug‐drug interaction prediction: A comprehensive review
di: Xinyue Li, et al.
Pubblicazione: (2024)

Evaluation of machine-learning models to measure individualized treatment effects from randomized clinical trial data with time-to-event outcomes
di: Roblin, Elvire, et al.
Pubblicazione: (2025)

Data Analysis and Modeling for Transitioning Between Laboratory Methods for Detecting SARS-CoV-2 in Wastewater
di: Warns, Maria M., et al.
Pubblicazione: (2025)

Drug-target interaction prediction by integrating heterogeneous information with mutual attention network
di: Zhang, Yuanyuan, et al.
Pubblicazione: (2024)

DDI‐Transform: A neural network for predicting drug‐drug interaction events
di: Jiaming Su, et al.
Pubblicazione: (2024)