Daniele Marinazzo
Biographic Data
| ID | 1751455 |
|---|---|
| NAME | Daniele Marinazzo |
| GIVEN NAMES | Daniele |
| FAMILY NAME | Marinazzo |
| SIGNATURE | MARINAZZO D |
| AFFILIATIONS | Ghent University |
| ORCID | 0000-0002-9803-0122 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 1 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 1 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Cognitive modelling of concepts in the mental lexicon with multilayer networks
The mental lexicon is a complex cognitive system representing information about the words/concepts that one knows. Over decades psychological experiments have shown that conceptual associations across multiple, interactive cognitive levels can greatly influence word acquisition, storage, and processing. How can semantic, phonological, syntactic, and other types of conceptual associations be mapped within a coherent mathematical framework to study…
Large language models surpass human experts in predicting neuroscience results
Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offer a solution. LLMs trained on the vast scientific literature could potentially integrate noisy yet interrelated findings to forecast novel results better than human experts. Here, to evaluate this possibility, we created BrainBench, a forward-looking benchmark for predi…
Estimating psychopathological networks
Network models, in which psychopathological disorders are conceptualized as a complex interplay of psychological and biological components, have become increasingly popular in the recent psychopathological literature (Borsboom, et. al., 2011). These network models often contain significant numbers of unknown parameters, yet the sample sizes available in psychological research are limited. As such, general assumptions about the true network are in…
Large language models surpass human experts in predicting neuroscience results
Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offer a solution. LLMs trained on the vast scientific literature could potentially integrate noisy yet interrelated findings to forecast novel results better than human experts. Here, to evaluate this possibility, we created BrainBench, a forward-looking benchmark for predi…
Estimating psychopathological networks
Network models, in which psychopathological disorders are conceptualized as a complex interplay of psychological and biological components, have become increasingly popular in the recent psychopathological literature (Borsboom, et. al., 2011). These network models often contain significant numbers of unknown parameters, yet the sample sizes available in psychological research are limited. As such, general assumptions about the true network are in…
Cognitive modelling of concepts in the mental lexicon with multilayer networks
The mental lexicon is a complex cognitive system representing information about the words/concepts that one knows. Over decades psychological experiments have shown that conceptual associations across multiple, interactive cognitive levels can greatly influence word acquisition, storage, and processing. How can semantic, phonological, syntactic, and other types of conceptual associations be mapped within a coherent mathematical framework to study…
Large language models surpass human experts in predicting neuroscience results
Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offer a solution. LLMs trained on the vast scientific literature could potentially integrate noisy yet interrelated findings to forecast novel results better than human experts. Here, to evaluate this possibility, we created BrainBench, a forward-looking benchmark for predi…
Psychology (3 works) · Cognitive science (2 works) · Computer Science (2 works) · Neuroscience (2 works) · Topic Modeling (2 works) · Advanced Text Analysis Techniques (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence (1 work) · Clinical Psychology (1 work) · Cognition (1 work)