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Found 8 papers, 3 papers with code
HLOB -- Information Persistence and Structure in Limit Order Books
We introduce a novel large-scale deep learning model for Limit Order Book mid-price changes forecasting, and we name it `HLOB'.
Deep Limit Order Book Forecasting
We exploit cutting-edge deep learning methodologies to explore the predictability of high-frequency Limit Order Book mid-price changes for a heterogeneous set of stocks traded on the NASDAQ exchange.
MindTheDApp: A Toolchain for Complex Network-Driven Structural Analysis of Ethereum-based Decentralised Applications
This paper presents MindTheDApp, a toolchain designed specifically for the structural analysis of Ethereum-based Decentralized Applications (DApps), with a distinct focus on a complex network-driven approach.
Homological Convolutional Neural Networks
Deep learning methods have demonstrated outstanding performances on classification and regression tasks on homogeneous data types (e. g., image, audio, and text data).
A Preliminary Analysis on the Code Generation Capabilities of GPT-3.5 and Bard AI Models for Java Functions
This paper evaluates the capability of two state-of-the-art artificial intelligence (AI) models, GPT-3. 5 and Bard, in generating Java code given a function description.
Cryptocurrency co-investment network: token returns reflect investment patterns
Finally, studying the co-investment network of currencies that share common investors, we show that assets with shared investors tend to be characterized by similar market behavior.
On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning
This work aims to analyse the predictability of price movements of cryptocurrencies on both hourly and daily data observed from January 2017 to January 2021, using deep learning algorithms.
SHARVOT: secret SHARe-based VOTing on the blockchain
In this paper, we discuss possible uses of the blockchain technology to implement a secure and fair voting system.
Computers and Society Cryptography and Security
