Difference between revisions of "Journal Club"
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== Articles == | == Articles == | ||
* [Aug 30, 2017] Shmuelof and Krakauer, 2011. Are we ready for a natural history of motor learning? [[Media:Journal_Club_Aug_30_2017.pdf]] [http://www.sciencedirect.com/science/article/pii/S0896627311009299 Paper] | * [Aug 30, 2017] Shmuelof and Krakauer, 2011. Are we ready for a natural history of motor learning? [[Media:Journal_Club_Aug_30_2017.pdf]] [http://www.sciencedirect.com/science/article/pii/S0896627311009299 Paper] | ||
| − | * [Sept 11, 2017] Thura and Cisek, 2017. The Basal Ganglia Do Not Select Reach | + | * [Sept 11, 2017] Thura and Cisek, 2017. The Basal Ganglia Do Not Select Reach Targets but Control the Urgency of Commitment. [[File:JC_Sept_11.pdf]] |
| − | Targets but Control the Urgency of Commitment. [[File:JC_Sept_11.pdf]] | + | |
[https://www.ncbi.nlm.nih.gov/pubmed/28823728 Paper] | [https://www.ncbi.nlm.nih.gov/pubmed/28823728 Paper] | ||
* [Jan 11, 2018] Munafò et al., 2017. A manifesto for reproducible science. [https://www.nature.com/articles/s41562-016-0021] | * [Jan 11, 2018] Munafò et al., 2017. A manifesto for reproducible science. [https://www.nature.com/articles/s41562-016-0021] | ||
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* [March 22, 2018] Dasgupta, Stevens, Navlakha, 2017. A neural algorithm for a fundamental computing problem. [http://science.sciencemag.org/content/358/6364/793] | * [March 22, 2018] Dasgupta, Stevens, Navlakha, 2017. A neural algorithm for a fundamental computing problem. [http://science.sciencemag.org/content/358/6364/793] | ||
| − | == Tutorials == | + | == NEW: Modern ML tutorials == |
| + | see Markdown slides and code [https://github.com/BlohmLab/MLtutorials here] | ||
| + | |||
| + | == Older Tutorials == | ||
* [[Media:MLintro.pdf | Machine learning introduction]] - Gunnar | * [[Media:MLintro.pdf | Machine learning introduction]] - Gunnar | ||
* [[Media:LinearRegression.pdf | Linear Regression]] - Sisi | * [[Media:LinearRegression.pdf | Linear Regression]] - Sisi | ||
* [[Media:Linear_Classification.pdf | Linear Classification]] - Parisa | * [[Media:Linear_Classification.pdf | Linear Classification]] - Parisa | ||
| − | * [[Media:MCMC.pdf | Markov Chain | + | * [[Media:MCMC.pdf | Markov Chain Monte Carlo]] - Gunnar |
* [[Media:Intro to PCA and ICA.pdf | Introduction to PCA and ICA]] - Cindy | * [[Media:Intro to PCA and ICA.pdf | Introduction to PCA and ICA]] - Cindy | ||
* [[Media:EM_algorithm.pdf | Expectation Maximization]] - Brandon and Jonathan | * [[Media:EM_algorithm.pdf | Expectation Maximization]] - Brandon and Jonathan | ||
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* [[Media:Support Vector Machines (SVM).pdf | Support Vector Machines]] - Jerry | * [[Media:Support Vector Machines (SVM).pdf | Support Vector Machines]] - Jerry | ||
* [[Media:Deep_Belief_Network_Home_(2).pdf | Deep belief networks ]] - Tiger | * [[Media:Deep_Belief_Network_Home_(2).pdf | Deep belief networks ]] - Tiger | ||
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Latest revision as of 19:36, 20 March 2020
Articles
- [Aug 30, 2017] Shmuelof and Krakauer, 2011. Are we ready for a natural history of motor learning? Media:Journal_Club_Aug_30_2017.pdf Paper
- [Sept 11, 2017] Thura and Cisek, 2017. The Basal Ganglia Do Not Select Reach Targets but Control the Urgency of Commitment. File:JC Sept 11.pdf
- [Jan 11, 2018] Munafò et al., 2017. A manifesto for reproducible science. [1]
- [March 8, 2018] Castañón et al., 2018 (preprint). Human noise blindness drives suboptimal cognitive inference. [2]
- [March 15, 2018] Odegaard et al., 2017. Superior colliculus neuronal ensemble activity signals optimal rather than subjective confidence. [3]
- [March 22, 2018] Dasgupta, Stevens, Navlakha, 2017. A neural algorithm for a fundamental computing problem. [4]
NEW: Modern ML tutorials
see Markdown slides and code here
Older Tutorials
- Machine learning introduction - Gunnar
- Linear Regression - Sisi
- Linear Classification - Parisa
- Markov Chain Monte Carlo - Gunnar
- Introduction to PCA and ICA - Cindy
- Expectation Maximization - Brandon and Jonathan
- Hidden Markov Models - Parisa
- Kalman filter - Josh
- Rate-based networks & error back-propagation learning - Scott
- Support Vector Machines - Jerry
- Deep belief networks - Tiger
