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Single-image super-resolution microscopy
A deep learning pre-trained model based on the Enhanced Super Resolution Generative Adversarial Network (ESRGAN) is used to obtain a Super-Resolution (SR) image from a...-
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Private jointfusion_hackathon
A joint fusion DL model was developed to predict ASD from structural and functional connectome brain features extracted form the ABIDE MRI and fMRI datasets. The DL algorithm... -
Private bone age assessment
The goal this DL model is to predict the age of a subject by looking at his/her X-ray image of the hand. This DL algorithm was developed to address a challenge posed on thee... -
AGC: Autism Graph Classifier
AGC is designed to support the processing and analysis of brain connectivity data by leveraging standard outputs from widely used neuroimaging pipelines such as CPAC and...-
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Private GreenBioNet
The methods contain a benchmarking pipeline for evaluating Graph Neural Networks (GNNs) across performance, energy consumption, and resource usage on heterogeneous hardware... -
Private Masking Models for Outlier Explanation (M2OE)
$\text{M}^2 \text{OE}$ - Masking Models for Outlier Explanation This repository provides a Python implementation of the Masking Models for Outlier Explanation ($\text{M}^2... -
Private LatentOut
Tensorflow Implementation of LatentOut This repository provides a Tensorflow implementation of the LatentOut framework for anomaly detection. It is an extension of VAEOut, an... -
Private AutoEncoder-based eXplainable Anomaly Detection (AE-XAD)
AE-XAD This repository contains the code of the AE-XAD method (authored by Fabrizio Angiulli, Fabio Fassetti, Luca Ferragina and Simona Nisticò). Dataset Dataset classes are... -
Private AE-SAD
Tensorflow implementation of AE-SAD This repository provides a Tensorflow implementation of the AE-SAD method for (semi-)supervised anomaly detection. Citation and Contact... -
AspenPlus: ASP-based Implementation for Collective Entity Resolution with Glo...
This is an Answer Set Programming (ASP) encoding for LACE+, which is a novel declarative approach to Collective Entity Resolution in the classical relational database setting,... -
Federated Recursive Ridge Regression
Official implementation of the Federated Recursive Ridge Regression (Fed3R) and Only Local Labels (OLL) algorithms proposed in the ICML24 accepted paper "Accelerating... -
ErNESTO-gym
Standardized micro-grid environment for reinforcement learning experiments employing real-world datasets regarding energy consumption, generation, and market.-
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CPG: Constrained Policy Gradient
CPG is a reinforcement learning algorithm thought for solving continuous control problems with user defined or structural constraints. CPG has two versions, C-PGPE and C-PGAE,... -
Best Arm Identification for Stochastic Rising Bandits
We propose two algorithms, R-UCBE and R-SR, performing best arm identification in the stochastic rising bandit setting, thought for modeling the combined algorithm selection... -
Artificial Graph Dataset Generator
This Python package generates synthetic graphs with a fixed graph edit distance. The generated datasets can be used to robustly train deep learning algorithms to compute the... -
Synchronization is All You Need - Exocentric-to-Egocentric Transfer for Tempo...
We consider the problem of transferring a temporal action segmentation system initially designed for exocentric (fixed) cameras to an egocentric scenario, where wearable... -
PREGO: Online mistake detection in PRocedural EGOcentric videos
Promptly identifying procedural errors from egocentric videos in an online setting is highly challenging and valuable for detecting mistakes as soon as they happen. This... -
EgoISM-HOI - Exploiting Multimodal Synthetic Data for Egocentric Human-Object...
We tackle the problem of Egocentric Human-Object Interaction (EHOI) detection in an industrial domain. To overcome the lack of public datasets in this context, we propose a... -
AFF-ttention! - Affordances and Attention models for Short-Term Object Intera...
Short-Term object-interaction Anticipation (STA) consists of detecting the location of the next-active objects, the noun and verb categories of the interaction, and the time... -
Private Neural2PC
Neural2PC is a novel machine-learning approach that finds polarized communities in signed networks. The method explores suboptimal solutions to the relaxed 2PC problem and...
