Welcome to MINDS!
Established in 2020, POSTECH Mathematical Institute for Data Science (MINDS) is the community of researchers in the areas of fundamental data science, machine learning, artificial intelligence, scientific computing, and humanitarian data science. MINDS mission is to provide a platform for collaboration among researchers and to provide various opportunities for students in data science. MINDS also aims to use our data science research to serve our local and global communities pursuing humanitarian data science.
News
🌟 DACON Ranker Special Lecture: Winning Strategies for AI Competitions 🌟
2023.11.30
3nd POSTECH&Peking SIAM Student Chapter Joint Conference
2023.11.01
2023 PSSC Summer Camp
2023.10.04
[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고]-상시모집
2023.07.25
[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고]
2023.07.14
[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구교수 채용 공고]
2023.06.12
Seminar | Joint seminar for probability and mathematical biology
2023.05.02
[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고]
2023.02.15
Upcoming Events
Schedule
MINDS SEMINAR
MINDS Seminar Series | Kyungmin Kim (Ewha Womans University) - Deep Learning-based Search for Microlensing Signature from Binary Black Hole Events in GWTC-1 and -2
MINDS SEMINAR
period : 2022-09-22 ~ 2022-09-22
time : 17:00:00 ~ 18:00
개최 장소 : Math Bldg 404 & Online streaming (Zoom)
Topic : Deep Learning-based Search for Microlensing Signature from Binary Black Hole Events in GWTC-1 and -2
개요
Date | 2022-09-22 ~ 2022-09-22 | Time | 17:00:00 ~ 18:00 |
Speaker | Kyungmin Kim | Affiliation | Ewha Womans University |
Place | Math Bldg 404 & Online streaming (Zoom) | Streaming link | ID : 688 896 1076 / PW : 54321 |
Topic | Deep Learning-based Search for Microlensing Signature from Binary Black Hole Events in GWTC-1 and -2 | ||
Contents | We present the result of the first deep learning-based endeavor for searching the signature of microlensing in gravitational waves. This search seeks the signature induced by lenses with masses between 10^3 M_sun - 10^5 M_sun from spectrograms of the binary black hole events in the first and second gravitational-wave transient catalogs. We use a deep learning model trained with spectrograms of simulated noisy gravitational-wave signals to classify the events into two classes, lensed or unlensed. We introduce ensemble learning and a majority voting-based consistency test for the predictions of ensemble learners. The classification scheme of this search primarily classifies one event, GW190707_093326, into the lensed class. We observe the median probability of the event, 0.984^{+0.012}_{-0.342}, agrees with an empirical criterion >0.6 for claiming the detection of a lensed signal. However, the uncertainty of the estimated p-value for the median probability and error, ranging from 0 to 0.1, convinces us GW190707_093326 is less likely a lensed event because it includes p >= 0.05 where the unlensed hypothesis is true. Therefore, we conclude our search finds no significant evidence of microlensing signature from the evaluated binary black hole events. |
MinDS
·
2022-09-02 10:28 ·
Views 833
POSTECH SIAM Student Chapter
🌟 DACON Ranker Special Lecture: Winning Strategies for AI Competitions 🌟
2023 POSTECH & Peking SIAM Student Chapter Joint Conference
2023 PSSC Summer Camp
2022 PSSC Summer Camp
2022 POSTECH & Peking SIAM Student Chapter Joint Conference
MINDS-MoNET-ISE Workshop
Information, Network & Topological Data Analysis
2021 POSTECH MINDS WORKSHOP
Recent Progress in Data Science and Applications
- Nov. 19(Fri) ~ Nov. 20(Sat) 2021 (1 Night 2 Days)
- Workshop homepage
Fall 2021 Seminar Series
MINDS Seminar Series on Data Science, Machine Learning, and Scientific Computing
Every Tuesdays 05:00 PM
ILJU POSTECH MINDS Workshop on TDA and ML
July 6 ~ July 9
Registration is required (please register here)