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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... -
Private ML-Link
ML-Link is a novel neural-network-based learning framework for link prediction on (attributed) multilayer networks, whose key idea is to combine (i) pairwise similarities of... -
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.... -
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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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... -
Private Multi-Start Optimization Neural Networks
In this repository, we publish the codes necessary to implement the Multi-Start Optimization Neural Networks (MSO-NNs), presented fin the paper: Automatic... -
Graph-Informed Neural Networks
In this repository, we publish the codes necessary to implement the Graph-Informed Neural Networks (GINNs), presented for the first time in the paper: Graph-Informed Neural... -
Private Alternate Training for Multi-Task Neural Networks
In this repository, we publish the code used to implement the Alternate Training through the Epochs (ATE) procedure for training Multi-Task Neural Networks (MTNN) presented in... -
Private Dynamical Linear Upper Confidence Bound (DynLin-UCB)
The repository contains the code to run DynLin-UCB (Dynamical Linear Upper Confidence Bound). DynLin-UCB is an optimistic regret-minimization algorithm that can be used to... -
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...
