3 citations · 5 across the 3 of their papers we have counts for
5 papers
Mapping Complex Technologies via Science-Technology Linkages; The Case of Neuroscience -- A transformer based keyword extraction approach
Daniel Hain, Roman Jurowetzki, Mariagrazia Squicciarini
In this paper, we present an efficient deep learning based approach to extract technology-related topics and keywords within scientific literature, and identify corresponding techn…
PatentSBERTa: A Deep NLP based Hybrid Model for Patent Distance and Classification using Augmented SBERT
Hamid Bekamiri, Daniel S. Hain, Roman Jurowetzki
This study provides an efficient approach for using text data to calculate patent-to-patent (p2p) technological similarity, and presents a hybrid framework for leveraging the resul…
The Privatization of AI Research(-ers): Causes and Potential Consequences -- From university-industry interaction to public research brain-drain?
Roman Jurowetzki, Daniel Hain, Juan Mateos-Garcia +1
The private sector is playing an increasingly important role in basic Artificial Intelligence (AI) R&D. This phenomenon, which is reflected in the perception of a brain drain of re…
An evolutionary view on the emergence of Artificial Intelligence
Matheus E. Leusin, Bjoern Jindra, Daniel S. Hain
This paper draws upon the evolutionary concepts of technological relatedness and knowledge complexity to enhance our understanding of the long-term evolution of Artificial Intellig…
Introduction to Rare-Event Predictive Modeling for Inferential Statisticians -- A Hands-On Application in the Prediction of Breakthrough Patents
Daniel Hain, Roman Jurowetzki
Recent years have seen a substantial development of quantitative methods, mostly led by the computer science community with the goal of developing better machine learning applicati…