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Neural Networks for Sparse Grid-Based Discontinuity Detectors
In this repository, we publish the codes necessary to load and use the NN-based discontinuity detectors, presented for the first time in the preprint: Graph-Informed Neural... -
Onboard deep lossless and near-lossless predictive coding of hyperspectral im...
Code for "Onboard deep lossless and near-lossless predictive coding of hyperspectral images with line-based attention" paper. The method implements a low-complexity neural... -
Private neuroAnDetect
Semi-supervised approach to anomaly detection for neuro-imaging. The method generates segmentation of abnormal tissues that can be used to support medical reporting. The... -
Private ASPen: ASP-based Implementation for Collective Entity Resolution
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.... -
The ProASP System
ProASP stands as the first compilation-based ASP solver specifically designed to efficiently evaluate ASP programs. Its evaluation techniques address the well-known grounding... -
Private Cybersecurity NER BERT-base-cased model
This method includes a Python script and files of a BERT-base-cased model fine-tuned on our Cybersecurity NER dataset. The method requires as input a list of sentences that... -
Cybersecurity NER RoBERTa-base model
This method includes a Python script and files of a RoBERTa-base model fine-tuned on our Cybersecurity NER dataset. The method requires as input a list of sentences that will...-
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Cybersecurity NER SecureBERT model
This method includes a Python script and files of a SecureBERT model fine-tuned on our Cybersecurity NER dataset. The method requires as input a list of sentences that will be...-
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Fuzzy Logic Visual Network (FLVN): A neuro-symbolic approach for visual featu...
Neuro-symbolic integration aims at harnessing the power of symbolic knowledge representation combined with the learning capabilities of deep neural networks. In particular,... -
Private ltlf2asp
Linear Temporal Logic over Finite Traces (LTLf) is a popular logic to reason about finite sequences of events. In LTLf, the (bounded) satisfiability problem refers to whether... -
Online Learning of Order Flow and Market Impact (OLOFMI)
This library performs regime detection in the aggregated order flow time-series and market impact analysis. The required input file is in the format of the message file of the... -
Score-Driven Bayesian Online Change Point Detection (SD-BOCPD)
This code deals with Bayesian online detection in univariate time-series of changepoints, i.e. abrupt variations in the generative parameters of a data, and regimes, i.e.... -
Reducing radicalizism in social networks by feeds prioritization - Rebalancin...
Code and description of the methodology of the paper "Rebalancing Social Feed to Minimize Polarization and Disagreement" funded by SoBigData ++ -
Gene-specific regularization for COPD partial-correlation estimation
We introduce a gene-specific regularization factor when computing the Partial Correlation score to make the indeterminate regression feasible. We decided to slightly modify... -
A New Topological Approach for the Prediction of Protein-Protein Interactions
We propose, Maximum-Proteins-Similarity(Topological)": MPS(T). MPS(T) is a topological three-length path method that scores the potential interaction between proteins by... -
A hybrid approach for PPI
We propose a new framework that can exploit topological and biological information to predict protein-protein interactions. The algorithm relies on the underlying hypothesis... -
EpiCID: A framework for discovering interactions between SNPs
Epistatic interactions (EIs) of gene loci often determine complex trait phenotypes. EIs may indicate the underlying molecular mechanisms of multifactorial traits and diseases.... -
Epidemic Sentiment Analysis
This tool is a sentiment analysis framework inspired by models of epidemic spreading, which aims to extend sentiment-tagged lexicons. It is easily extendable to multiple... -
Prediction of next career moves from scientific profiles
This is a two-stage predictive model for the mobility of scientists. First, data mining is used to predict which researcher will move in the next year on the basis of their... -
Economic Integration Model
This model allows to understand the integration process of immigrants starting from retail data. Under development.
