Difference between revisions of "Journal Club"
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* [March 8, 2018] Castañón et al., 2018 (preprint). Human noise blindness drives suboptimal cognitive inference. [https://www.biorxiv.org/content/early/2018/02/19/268045] | * [March 8, 2018] Castañón et al., 2018 (preprint). Human noise blindness drives suboptimal cognitive inference. [https://www.biorxiv.org/content/early/2018/02/19/268045] | ||
* [March 15, 2018] Odegaard et al., 2017. Superior colliculus neuronal ensemble activity signals optimal rather than subjective confidence. [http://www.pnas.org/content/115/7/E1588.long] | * [March 15, 2018] Odegaard et al., 2017. Superior colliculus neuronal ensemble activity signals optimal rather than subjective confidence. [http://www.pnas.org/content/115/7/E1588.long] | ||
| − | * [March 22, 2018] Dasgupta, Stevens, Navlakha, 2017. A neural algorithm for a fundamental computing problem. [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 == | == Tutorials == | ||
Revision as of 19:07, 4 April 2018
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 Paper
- [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]
Tutorials
- Machine learning introduction - Gunnar
- Linear Regression - Sisi
- Linear Classification - Parisa
- Markov Chain Montre 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
Proposed
- ...
