no code implementations • 8 Jan 2024 • Robin Thériault, Daniele Tantari
Dense Hopfield networks are known for their feature to prototype transition and adversarial robustness.
no code implementations • 26 Apr 2023 • Francesco Alemanno, Luca Camanzi, Gianluca Manzan, Daniele Tantari
While Hopfield networks are known as paradigmatic models for memory storage and retrieval, modern artificial intelligence systems mainly stand on the machine learning paradigm.
no code implementations • 14 Apr 2022 • Alessio Brini, Gabriele Tedeschi, Daniele Tantari
The policy recommendation directs economic actors to create credit relationships through the optimal choice between a low interest rate or a high liquidity supply.
1 code implementation • 29 Apr 2021 • Alessio Brini, Daniele Tantari
Classical portfolio optimization often requires forecasting asset returns and their corresponding variances in spite of the low signal-to-noise ratio provided in the financial markets.
no code implementations • 31 Aug 2020 • Giovanni Calice, Carlo Sala, Daniele Tantari
We study the role of contingent convertible bonds (CoCos) in a complex network of interconnected banks.
no code implementations • 24 Aug 2020 • Carlo Campajola, Fabrizio Lillo, Piero Mazzarisi, Daniele Tantari
Binary random variables are the building blocks used to describe a large variety of systems, from magnetic spins to financial time series and neuron activity.
Statistical Mechanics Econometrics Data Analysis, Statistics and Probability
1 code implementation • 30 Jul 2020 • Carlo Campajola, Domenico Di Gangi, Fabrizio Lillo, Daniele Tantari
A common issue when analyzing real-world complex systems is that the interactions between the elements often change over time: this makes it difficult to find optimal models that describe this evolution and that can be estimated from data, particularly when the driving mechanisms are not known.
no code implementations • 24 Sep 2019 • Carlo Campajola, Fabrizio Lillo, Daniele Tantari
We propose a method to infer lead-lag networks of traders from the observation of their trade record as well as to reconstruct their state of supply and demand when they do not trade.
no code implementations • 30 Dec 2017 • Piero Mazzarisi, Paolo Barucca, Fabrizio Lillo, Daniele Tantari
We propose a dynamic network model where two mechanisms control the probability of a link between two nodes: (i) the existence or absence of this link in the past, and (ii) node-specific latent variables (dynamic fitnesses) describing the propensity of each node to create links.
no code implementations • 20 Feb 2017 • Adriano Barra, Giuseppe Genovese, Peter Sollich, Daniele Tantari
Restricted Boltzmann Machines are described by the Gibbs measure of a bipartite spin glass, which in turn corresponds to the one of a generalised Hopfield network.
no code implementations • 20 Jan 2017 • Paolo Barucca, Fabrizio Lillo, Piero Mazzarisi, Daniele Tantari
We analytically and numerically characterize the detectability transitions of such algorithm as a function of the memory parameters of the model and we make a comparison with a full dynamic inference.
no code implementations • 9 Dec 2016 • Adriano Barra, Giuseppe Genovese, Peter Sollich, Daniele Tantari
We study Generalised Restricted Boltzmann Machines with generic priors for units and weights, interpolating between Boolean and Gaussian variables.