Speaker：Prof. Konrad K?rding, Neuroscience, Bioengineering, University of Pennsylvania
Time：15:00-16:30, July 21, 2024
Venue：Room 1113， Wangkezhen Building
Host：Prof. Kunlin Wei
Abstract
In this talk, I will review how we can infer causality, how one variable affects another. I will start building an intuition for the general problem occurring in statistical inference. I will highlight how this is a major problem for significant branches of neuroscience. I will then also review quasi-experimental methods that sometimes allow successful causal identification. Lastly, Iwil introduce a new class of causal inference algorithms that promise to outperform previous algorithms.
Bio
研究聚焦于計(jì)算神經(jīng)科學(xué) ，通過數(shù)據(jù)來研究大腦的運(yùn)作方式。早期研究關(guān)注 感知和運(yùn)動(dòng)方面，近年來從數(shù)據(jù)科學(xué)出發(fā)，在大腦功能、深度學(xué)習(xí)、個(gè)性化 醫(yī)療等諸多領(lǐng)域開展研究包括逆向工程完整神經(jīng)系統(tǒng)等新方向。同時(shí)K?rding教授是開放科學(xué)(open science)的主要推動(dòng)者之一，計(jì)算神經(jīng)科學(xué)的在線學(xué)校 Neuromatch的主要?jiǎng)?chuàng)立者。
2024-07-15