Flashcards
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Cards in this deck (25)
- 1Goodfellow, Deep Learninga
- 2What is the true challenge of AI according to the authors?s
- 3Why is deep learning called deep learning (according to authors)?s
- 4What are deep learning, representation learning, machine learning, and AI and how do they relate to each other?s
- 5Is deep learning really new, or not? And why?s
- 6Be able to recognize the various names that are used for and associated with neural networks as discussed in section 1.2.1s
- 7Are deep learning models truly a model of the brain (i.e. inspired by neuroscience) or not?s
- 8Are deep learning models the “killer solution” to all cognitive science at this time?s
- 9How do increases in dataset size and model sizes explain the recent success of deep learning models?s
- 10Can we expect deep learning networks to cover all aspects of the human brain soon?s
- 11McClellands
- 12What’s the purpose of modeling in Cognitive Science according to McClelland?s
- 13Why is simplification essential?s
- 14What are downsides of simplifications?s
- 15Why was the invention of the computer essential for cognitive science? And what were limitations to this?s
- 16Why is care needed when interpreting successes and failures of models?s
- 17How should a cognitive model be judged (according to McClelland)s
- 18Understand McClelland’s take on Popper (i.e., modeling as “existence proof”)s
- 19What is McClelland’s criticism on Marr’s levels approach?s
- 20What does McClelland see as trends (&future) in cognitive modeling?s
- 21General Q'ss
- 22Understand the various ways of classification & be able to apply them to case studies (i.e., be able to classify a model yourself)s
- 23Understand the downward, upward, inward, outward framework and be able to apply this to case studiess
- 24Understand how Process, Bayesian, and Machine Learning models are positioned relative to each other and in the wider field of cognitive modelings
- 25Understand current developments and (projected) future directions of the fields
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- Flashcards on Untitled, created by August Edström on 24/01/2019.
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- August Edström
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