research
∙
10/24/2022
Occam learning
We discuss probabilistic neural network models for unsupervised learning...
share
research
∙
02/01/2022
Quantifying Relevance in Learning and Inference
Learning is a distinctive feature of intelligent behaviour. High-through...
research
∙
12/17/2021
A random energy approach to deep learning
We study a generic ensemble of deep belief networks which is parametrize...
research
∙
08/02/2020
Statistical Inference of Minimally Complex Models
Finding the best model that describes a high dimensional dataset, is a d...
research
∙
06/12/2020
Characterising authors on the extent of their paper acceptance: A case study of the Journal of High Energy Physics
New researchers are usually very curious about the recipe that could acc...
research
∙
06/08/2020
Optimal Work Extraction and the Minimum Description Length Principle
We discuss work extraction from classical information engines (e.g., Szi...
research
∙
11/05/2019
Thermodynamic Computing
The hardware and software foundations laid in the first half of the 20th...
research
∙
03/01/2019
On the complexity of logistic regression models
We investigate the complexity of logistic regression models which is def...
research
∙
09/03/2018
Minimum Description Length codes are critical
Learning from the data, in Minimum Description Length (MDL), is equivale...
research
∙
05/02/2017
Influence of Reviewer Interaction Network on Long-term Citations: A Case Study of the Scientific Peer-Review System of the Journal of High Energy Physics
A `peer-review system' in the context of judging research contributions,...
research
∙
02/24/2017
The Stochastic complexity of spin models: How simple are simple spin models?
Simple models, in information theoretic terms, are those with a small st...
research
∙
03/03/2016