:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Barbato, Mirko Paolo, Rigamonti, Giorgia, Marelli, Davide, Napoletano, Paolo
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2506.07864
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tailoring Adverse Event Prediction in Type 1 Diabetes with Patient-Specific Deep Learning Models
by: Rigamonti, Giorgia, et al.
Published: (2026)

The ISLab Solution to the Algonauts Challenge 2025: A Multimodal Deep Learning Approach to Brain Response Prediction
by: Corsico, Andrea, et al.
Published: (2025)

Glycemic-Aware and Architecture-Agnostic Training Framework for Blood Glucose Forecasting in Type 1 Diabetes
by: Khamesian, Saman, et al.
Published: (2025)

Privacy Preserved Blood Glucose Level Cross-Prediction: An Asynchronous Decentralized Federated Learning Approach
by: Piao, Chengzhe, et al.
Published: (2024)

A Multitask VAE for Time Series Preprocessing and Prediction of Blood Glucose Level
by: AbuSaleh, Ali, et al.
Published: (2024)

GARNN: An Interpretable Graph Attentive Recurrent Neural Network for Predicting Blood Glucose Levels via Multivariate Time Series
by: Piao, Chengzhe, et al.
Published: (2024)

Improving Image Captioning Descriptiveness by Ranking and LLM-based Fusion
by: Celona, Luigi, et al.
Published: (2023)

AttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset
by: Farahmand, Ebrahim, et al.
Published: (2025)

Blood Glucose Level Prediction in Type 1 Diabetes Using Machine Learning
by: Chu, Soon Jynn, et al.
Published: (2025)

A Physiologically-Constrained Neural Network Digital Twin Framework for Replicating Glucose Dynamics in Type 1 Diabetes
by: Roquemen-Echeverri, Valentina, et al.
Published: (2025)

MATNet: Multi-Level Fusion Transformer-Based Model for Day-Ahead PV Generation Forecasting
by: Tortora, Matteo, et al.
Published: (2023)

Predicting Blood Type: Assessing Model Performance with ROC Analysis
by: Altayar, Malik A., et al.
Published: (2025)

seqBench: A Tunable Benchmark to Quantify Sequential Reasoning Limits of LLMs
by: Ramezanali, Mohammad, et al.
Published: (2025)

Flexible Blood Glucose Control: Offline Reinforcement Learning from Human Feedback
by: Emerson, Harry, et al.
Published: (2025)

Blood Glucose Control Via Pre-trained Counterfactual Invertible Neural Networks
by: Jiang, Jingchi, et al.
Published: (2024)

MARIA: a Multimodal Transformer Model for Incomplete Healthcare Data
by: Caruso, Camillo Maria, et al.
Published: (2024)

Phase-Type Variational Autoencoders for Heavy-Tailed Data
by: Ziani, Abdelhakim, et al.
Published: (2026)

The Driver-Blindness Phenomenon: Why Deep Sequence Models Default to Autocorrelation in Blood Glucose Forecasting
by: Shakeri, Heman
Published: (2025)

Collaborative Learning-Enhanced Lightweight Models for Predicting Arterial Blood Pressure Waveform in a Large-scale Perioperative Dataset
by: Li, Wentao, et al.
Published: (2025)

GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals
by: Arefeen, Asiful, et al.
Published: (2025)

PhysioSeq2Seq: A Hybrid Physiological Digital Twin and Sequence-to-Sequence LSTM for Long-Horizon Glucose Forecasting in Type 1 Diabetes
by: Tran, Phat, et al.
Published: (2026)

FBFL: A Field-Based Coordination Approach for Data Heterogeneity in Federated Learning
by: Domini, Davide, et al.
Published: (2025)

Clover: Regressive Lightweight Speculative Decoding with Sequential Knowledge
by: Xiao, Bin, et al.
Published: (2024)

Scaling Sequential Recommendation Models with Transformers
by: Zivic, Pablo, et al.
Published: (2024)

A Benchmark of Causal vs. Correlation AI for Predictive Maintenance
by: Dhande, Shaunak, et al.
Published: (2025)

Proximity-based Self-Federated Learning
by: Domini, Davide, et al.
Published: (2024)

Crystalite: A Lightweight Transformer for Efficient Crystal Modeling
by: Veljković, Tin Hadži, et al.
Published: (2026)

Causify DataFlow: A Framework For High-performance Machine Learning Stream Computing
by: Saggese, Giacinto Paolo, et al.
Published: (2025)

MAVRL: Learning Reward Functions from Multiple Feedback Types with Amortized Variational Inference
by: Baur, Raphaël, et al.
Published: (2026)

A Large Sensor Foundation Model Pretrained on Continuous Glucose Monitor Data for Diabetes Management
by: Luo, Junjie, et al.
Published: (2024)

Uncertainty Estimation by Human Perception versus Neural Models
by: Mendes, Pedro, et al.
Published: (2025)

CLUE: Neural Networks Calibration via Learning Uncertainty-Error alignment
by: Mendes, Pedro, et al.
Published: (2025)

Leveraging GPT-4o Efficiency for Detecting Rework Anomaly in Business Processes
by: Derakhshan, Mohammad, et al.
Published: (2025)

Spatiotemporal Convolutions on EEG signal -- A Representation Learning Perspective on Efficient and Explainable EEG Classification with Convolutional Neural Nets
by: Dixen, Laurits, et al.
Published: (2026)

Markov Chain Decoders Overcome the Heavy-Tail Limitations of Lipschitz Generative Models
by: Ziani, Abdelhakim, et al.
Published: (2026)

Probabilistic ML Verification via Weighted Model Integration
by: Morettin, Paolo, et al.
Published: (2024)

Understanding the Training and Generalization of Pretrained Transformer for Sequential Decision Making
by: Wang, Hanzhao, et al.
Published: (2024)

Dynamic Hypergraph-Enhanced Prediction of Sequential Medical Visits
by: Yang, Wangying, et al.
Published: (2024)

fluke: Federated Learning Utility frameworK for Experimentation and research
by: Polato, Mirko
Published: (2024)

Optimizing Blood Transfusions and Predicting Shortages in Resource-Constrained Areas
by: Belfarsi, El Arbi, et al.
Published: (2025)