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
研究聚焦于計算神經(jīng)科學 ，通過數(shù)據(jù)來研究大腦的運作方式。早期研究關注 感知和運動方面，近年來從數(shù)據(jù)科學出發(fā)，在大腦功能、深度學習、個性化 醫(yī)療等諸多領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K?rding教授是開放科學(open science)的主要推動者之一，計算神經(jīng)科學的在線學校 Neuromatch的主要創(chuàng)立者。
