Nikolaus Kriegeskorte
Biographic Data
| ID | 1856119 |
|---|---|
| NAME | Nikolaus Kriegeskorte |
| GIVEN NAMES | Nikolaus |
| FAMILY NAME | Kriegeskorte |
| SIGNATURE | KRIEGESKORTE N |
| AFFILIATIONS | Columbia University |
| ORCID | 0000-0001-7433-9005 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2009 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
The Emergent Basis of Expert Trust
Goldman (2001) asks how novices can trust putative experts when background knowledge is scarce. We develop a reinforcement-learning model, adapted from Barrett, Skyrms, and Mohseni (2019), in which trust arises from experience rather than prior expertise labels. Agents incrementally weight peers who outperform them. Using a large dataset of human probability judgments as inputs, we simulate communities that learn whom to defer to. Both a strictly…
Semantic Data Set Construction from Human Clustering and Spatial Arrangement
Research into representation learning models of lexical semantics usually utilizes some form of intrinsic evaluation to ensure that the learned representations reflect human semantic judgments. Lexical semantic similarity estimation is a widely used evaluation method, but efforts have typically focused on pairwise judgments of words in isolation, or are limited to specific contexts and lexical stimuli. There are limitations with these approaches …
The representational dynamics of perceived voice emotions evolve from categories to dimensions
Capturing the objects of vision with neural networks
Circular analysis in systems neuroscience
Semantic Data Set Construction from Human Clustering and Spatial Arrangement
Research into representation learning models of lexical semantics usually utilizes some form of intrinsic evaluation to ensure that the learned representations reflect human semantic judgments. Lexical semantic similarity estimation is a widely used evaluation method, but efforts have typically focused on pairwise judgments of words in isolation, or are limited to specific contexts and lexical stimuli. There are limitations with these approaches …
Capturing the objects of vision with neural networks
Circular analysis in systems neuroscience
Semantic Data Set Construction from Human Clustering and Spatial Arrangement
Research into representation learning models of lexical semantics usually utilizes some form of intrinsic evaluation to ensure that the learned representations reflect human semantic judgments. Lexical semantic similarity estimation is a widely used evaluation method, but efforts have typically focused on pairwise judgments of words in isolation, or are limited to specific contexts and lexical stimuli. There are limitations with these approaches …
The representational dynamics of perceived voice emotions evolve from categories to dimensions
Capturing the objects of vision with neural networks
The Emergent Basis of Expert Trust
Goldman (2001) asks how novices can trust putative experts when background knowledge is scarce. We develop a reinforcement-learning model, adapted from Barrett, Skyrms, and Mohseni (2019), in which trust arises from experience rather than prior expertise labels. Agents incrementally weight peers who outperform them. Using a large dataset of human probability judgments as inputs, we simulate communities that learn whom to defer to. Both a strictly…
Computer Science (3 works) · Face Recognition and Perception (3 works) · Psychology (3 works) · Artificial Intelligence (2 works) · Cognitive psychology (2 works) · Neural dynamics and brain function (2 works) · Neuroscience (2 works) · Perception (2 works) · Ambiguity (1 works) · Amodal perception (1 works)