Congrats to @AkiNikolaidis et al. for helping to inform ‘Risk Factors Contributing to Youth Mental Health Symptoms During the Pandemic’ in the U.S. Surgeon General’s advisory report: “Protecting Youth Mental Health”
https://t.co/oNPSoE0CVQ
https://t.co/SN6gVE0IOs
What is the next stumbling block for neuroscience in achieving reproducible brain-behavior relationships? A sobering look at how differences in processing pipelines and seemingly innocuous decisions can drive findings apart, as well as potential solutions
https://t.co/310EUxLJYd
🚨Don’t miss this!
Reverse engineering the Brain
#MAIN2021 Nov 29 with the amazing:
James DiCarlo @JamesJDiCarlo
Surya Ganguli @SuryaGanguli
Joshua Vogelstein @neuro_data
Irina Rish @irinarish
Mod by Paul Cisek (Université de Montréal)
👇
I got an R01 grant! Looking for a post-doc and a research assistant interested in functional connectome in different species (e.g., macaque, humans, etc.)🧠🐭🐵🦧😀👽. Please help to spread! Apply link 👇 Thank you!
My first paper is finally published! This article is the culmination of my undergrad work in the @SombersLab that I completed with @kizzer1102 and @neuro_crandall. This project and my wonderful mentors got me where I am today and I’m stoked to finally share it with the world!
This reminds me of what I like about research.
I'm more interested in research that tries to solve problems that had not been possible before (0→1), and less interested in research that incrementally improves the performance metrics of well-studied tasks.https://t.co/OqzkkP2g3M
What are batch effects, how are they problematic, and what can we do about them? Where are the shortcomings in our existing understandings of batch effects, and how can we better aggregate data across sites? @neuro_data@MilhamMichael@g_kiar 1/11 https://t.co/7Bt3VgQHrR
Wow, our technical report is trending on @Deep__AI ! Thank you all for your support!
“When are Deep Networks really better than Random Forests at small sample sizes?” with Michael Ainsworth, Yu-Chung Peng, Madi Kusmanov, @bitapanda and @neuro_data https://t.co/ibkLMtZDSH
“When are Deep Networks really better than Random Forests at small sample sizes?” Posted preliminary works on RF vs DN comparisons across tabular, image, and audio domains. With Michael Ainsworth, Yu-Chung Peng, Madi Kusmanov, @bitapanda and @neuro_data https://t.co/iL0NB74N8O