What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Machine learning
His primary scientific interests are in Artificial intelligence, Visual cortex, Pattern recognition, Self-organizing map and Neuroscience.
His Artificial intelligence research includes themes of Machine learning and Computer vision.
Within one scientific family, Klaus Obermayer focuses on topics pertaining to Receptive field under Visual cortex, and may sometimes address concerns connected to Cortex, Macaque and Visual space.
The study incorporates disciplines such as Orientation, Feature and Matched filter in addition to Pattern recognition.
His Self-organizing map research incorporates elements of Vector quantization, Statistical physics, Function, Rate of convergence and Unit interval.
The concepts of his Neuroscience study are interwoven with issues in Biological system and Computation.
His most cited work include:
- Support vector learning for ordinal regression (388 citations)
- Self-organizing maps: ordering, convergence properties and energy functions (356 citations)
- Geometry of orientation and ocular dominance columns in monkey striate cortex (293 citations)
What are the main themes of his work throughout his whole career to date?
Klaus Obermayer mostly deals with Artificial intelligence, Neuroscience, Pattern recognition, Visual cortex and Computer vision.
The Artificial intelligence study combines topics in areas such as Algorithm and Machine learning.
His Algorithm study frequently draws connections between related disciplines such as Cluster analysis.
His study involves Excitatory postsynaptic potential, Inhibitory postsynaptic potential, Macaque, Striate cortex and Neuron, a branch of Neuroscience.
Feature vector is the focus of his Pattern recognition research.
His Visual cortex research incorporates themes from Stimulus, Network model and Receptive field.
He most often published in these fields:
- Artificial intelligence (37.63%)
- Neuroscience (22.89%)
- Pattern recognition (15.79%)
What were the highlights of his more recent work (between 2014-2021)?
- Neuroscience (22.89%)
- Artificial intelligence (37.63%)
- Neuron (5.53%)
In recent papers he was focusing on the following fields of study:
Neuroscience, Artificial intelligence, Neuron, Stimulus and Pattern recognition are his primary areas of study.
Neuroscience and Synaptic cleft are commonly linked in his work.
Artificial intelligence connects with themes related to Computer vision in his study.
The various areas that Klaus Obermayer examines in his Stimulus study include Expectancy theory, Weighting, Visual cortex and Amygdala.
His research in Visual cortex intersects with topics in Visual processing, Behavioral choice and Bursting.
His studies examine the connections between Pattern recognition and genetics, as well as such issues in Macaque, with regards to Decoding methods and Coding.
Between 2014 and 2021, his most popular works were:
- Bayes optimal template matching for spike sorting --- combining fisher discriminant analysis with optimal filtering (60 citations)
- Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation. (39 citations)
- From in silico astrocyte cell models to neuron-astrocyte network models: A review. (28 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Machine learning
His main research concerns Artificial intelligence, Neuroscience, Artificial neural network, Neuron and Biological system.
He combines subjects such as State, Computer vision and Pattern recognition with his study of Artificial intelligence.
His work in the fields of Neuroscience, such as Prefrontal cortex and Endophenotype, overlaps with other areas such as Alcohol dependence and Ventral striatum.
His studies deal with areas such as Pairwise comparison, Pseudolikelihood and Neural decoding as well as Artificial neural network.
His Neuron study incorporates themes from Network model, Synaptic cleft, Inhibitory postsynaptic potential, Computational model and Tripartite synapse.
Klaus Obermayer has researched Biological system in several fields, including Bayes estimator and Covariance.
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