VS265: Reading: Difference between revisions
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* [http://www.aiai.ed.ac.uk/events/lighthill1973/1973-BBC-Lighthill-Controversy.mov 1973 Lighthill debate on future of AI] | * [http://www.aiai.ed.ac.uk/events/lighthill1973/1973-BBC-Lighthill-Controversy.mov 1973 Lighthill debate on future of AI] | ||
Optional: | Optional: | ||
* Land, MF and Fernald, RD. [http://redwood.berkeley.edu/vs265/landfernald92.pdf The Evolution of Eyes], Ann Revs Neuro, 1992. | |||
* Zhang K, Sejnowski TJ (2000) [http://redwood.berkeley.edu/vs265/zhang-sejnowski.pdf A universal scaling law between gray matter and white matter of cerebral cortex.] PNAS, 97: 5621–5626. | |||
* O'Rourke, N.A et al. [http://redwood.berkeley.edu/vs265/smith-synaptic-diversity.pdf "Deep molecular diversity of mammalian synapses: why it matters and how to measure it."] Nature Reviews Neurosci. 13, (2012) | * O'Rourke, N.A et al. [http://redwood.berkeley.edu/vs265/smith-synaptic-diversity.pdf "Deep molecular diversity of mammalian synapses: why it matters and how to measure it."] Nature Reviews Neurosci. 13, (2012) | ||
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* '''HKP''' chapter 5, '''DJCM''' chapters 38-40 | * '''HKP''' chapter 5, '''DJCM''' chapters 38-40 | ||
* Mead, C. [http://redwood.berkeley.edu/vs265/Mead-intro.pdf Chapter 1: Introduction] and [http://redwood.berkeley.edu/vs265/Mead-neurons.pdf Chapter 4: Neurons] from ''Analog VLSI and Neural Systems'', Addison-Wesley, 1989. | * Mead, C. [http://redwood.berkeley.edu/vs265/Mead-intro.pdf Chapter 1: Introduction] and [http://redwood.berkeley.edu/vs265/Mead-neurons.pdf Chapter 4: Neurons] from ''Analog VLSI and Neural Systems'', Addison-Wesley, 1989. | ||
* [http://redwood.berkeley.edu/vs265/lti-conv/lti-convolution.html Linear time-invariant systems and convolution] | * [http://redwood.berkeley.edu/vs265/lti-conv/lti-convolution.html Linear time-invariant systems and convolution] | ||
* [http://redwood.berkeley.edu/vs265/diffeq-sim/diffeq-sim.html Simulating differential equations] | * [http://redwood.berkeley.edu/vs265/diffeq-sim/diffeq-sim.html Simulating differential equations] | ||
* [http://redwood.berkeley.edu/vs265/dynamics/dynamics.html Dynamics] | * [http://redwood.berkeley.edu/vs265/dynamics/dynamics.html Dynamics] | ||
Optional | |||
* Carandini M, Heeger D (1994) [http://redwood.berkeley.edu/vs265/carandini-heeger.pdf Summation and division by neurons in primate visual cortex.] Science, 264: 1333-1336. | * Carandini M, Heeger D (1994) [http://redwood.berkeley.edu/vs265/carandini-heeger.pdf Summation and division by neurons in primate visual cortex.] Science, 264: 1333-1336. | ||
==== 4 Sept ==== | ==== 4 Sept ==== | ||
* | * '''HKP''' chapter 6, '''DJCM''' chapters 38-40, 44, '''DA''' chapter 8 (sec. 4-6) | ||
* Jordan, M.I. [http://redwood.berkeley.edu/vs265/PDP.pdf An Introduction to Linear Algebra in Parallel Distributed Processing] in McClelland and Rumelhart, ''Parallel Distributed Processing'', MIT Press, 1985. | |||
* [http://redwood.berkeley.edu/vs265/linear-neuron/linear-neuron-models.html Linear neuron models] | |||
* [http://redwood.berkeley.edu/vs265/linear-algebra/linear-algebra.html Linear algebra primer] | |||
* [http://redwood.berkeley.edu/vs265/superlearn_handout1.pdf Handout] on supervised learning in single-stage feedforward networks | |||
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* '''Reading''': '''HKP''' chapter 8, '''DJCM''' chapter 36, '''DA''' chapter 8, 10 --> | * '''Reading''': '''HKP''' chapter 8, '''DJCM''' chapter 36, '''DA''' chapter 8, 10 --> | ||
<!-- plasticity and cortical maps | |||
* '''Reading''': '''HKP''' chapter 9, '''DA''' chapter 8 --> | |||
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* '''Reading''': '''HKP''' chapters 2, 3 (sec. 3.3-3.5), 7 (sec. 7.2-7.3), '''DJCM''' chapter 42, '''DA''' chapter 7 --> | |||
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* '''Reading''': '''HKP''' chapter 7 (sec. 7.1),'''DJCM''' chapter 1-3, 20-24,41,43, '''DA''' chapter 10 --> | |||
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* '''Reading''': '''DA''' chapter 1-4, 5.4 --> | |||
Revision as of 04:37, 1 September 2014
28 Aug
- HKP chapter 1
- Dreyfus, H.L. and Dreyfus, S.E. Making a Mind vs. Modeling the Brain: Artificial Intelligence Back at a Branchpoint. Daedalus, Winter 1988.
- Bell, A.J. Levels and loops: the future of artificial intelligence and neuroscience. Phil Trans: Bio Sci. 354:2013--2020 (1999) here or here
- 1973 Lighthill debate on future of AI
Optional:
- Land, MF and Fernald, RD. The Evolution of Eyes, Ann Revs Neuro, 1992.
- Zhang K, Sejnowski TJ (2000) A universal scaling law between gray matter and white matter of cerebral cortex. PNAS, 97: 5621–5626.
- O'Rourke, N.A et al. "Deep molecular diversity of mammalian synapses: why it matters and how to measure it." Nature Reviews Neurosci. 13, (2012)
2 Sept
- HKP chapter 5, DJCM chapters 38-40
- Mead, C. Chapter 1: Introduction and Chapter 4: Neurons from Analog VLSI and Neural Systems, Addison-Wesley, 1989.
- Linear time-invariant systems and convolution
- Simulating differential equations
- Dynamics
Optional
- Carandini M, Heeger D (1994) Summation and division by neurons in primate visual cortex. Science, 264: 1333-1336.
4 Sept
- HKP chapter 6, DJCM chapters 38-40, 44, DA chapter 8 (sec. 4-6)
- Jordan, M.I. An Introduction to Linear Algebra in Parallel Distributed Processing in McClelland and Rumelhart, Parallel Distributed Processing, MIT Press, 1985.
- Linear neuron models
- Linear algebra primer
- Handout on supervised learning in single-stage feedforward networks
