What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Cognition
- Neuroscience
Randall C. O'Reilly mainly focuses on Cognition, Neuroscience, Cognitive psychology, Cognitive science and Prefrontal cortex.
Randall C. O'Reilly is interested in Connectionism, which is a branch of Cognition.
His research combines Schizophrenia and Neuroscience.
His Cognitive psychology research is multidisciplinary, incorporating perspectives in Neocortex, First episode and Procedural memory.
His Cognitive science research focuses on Memoria and how it connects with Recognition memory.
He has researched Hippocampus in several fields, including Spatial view cells and Multiple trace theory.
His most cited work include:
- Why there are complementary learning systems in the hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory. (3620 citations)
- By Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism (1500 citations)
- Modeling hippocampal and neocortical contributions to recognition memory: a complementary-learning-systems approach. (991 citations)
What are the main themes of his work throughout his whole career to date?
Randall C. O'Reilly mainly investigates Cognition, Neuroscience, Artificial intelligence, Cognitive science and Cognitive psychology.
His work in the fields of Cognition, such as Connectionism, intersects with other areas such as Control.
He focuses mostly in the field of Neuroscience, narrowing it down to topics relating to Recall and, in certain cases, Recognition memory.
His study in the field of Artificial neural network and Cognitive neuroscience of visual object recognition is also linked to topics like Leabra and SIGNAL.
The Cognitive science study which covers Cognitive model that intersects with Rational analysis.
The study incorporates disciplines such as Memoria, Cognitive neuropsychology, Pattern completion and Self-reference effect in addition to Cognitive psychology.
He most often published in these fields:
- Cognition (32.93%)
- Neuroscience (32.93%)
- Artificial intelligence (31.14%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (31.14%)
- Cognition (32.93%)
- Artificial neural network (19.76%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, Cognition, Artificial neural network, Natural language processing and Outcome are his primary areas of study.
His Artificial intelligence study incorporates themes from Machine learning and Pattern recognition.
His Cognition research includes themes of Cognitive science and Computational model.
His Cognitive science research integrates issues from Representation, Neuroscience research and Dorsolateral prefrontal cortex.
His Computational model research incorporates elements of Computational neuroscience and Working memory.
His Basal ganglia study contributes to a more complete understanding of Neuroscience.
Between 2017 and 2021, his most popular works were:
- Compositional generalization in a deep seq2seq model by separating syntax and semantics. (29 citations)
- Unraveling the Mysteries of Motivation (4 citations)
- Learning Representations that Support Extrapolation (3 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Cognition
- Neuroscience
His scientific interests lie mostly in Artificial intelligence, Heuristic, Syntax, Structure and Deep learning.
His Artificial intelligence research is multidisciplinary, incorporating elements of Neocortex and Sensory system.
His studies deal with areas such as Machine translation, Natural language processing, Semantic learning, Translation and Semantic memory as well as Heuristic.
His research ties Semantics and Syntax together.
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