Preserving History at Cyark
Data Skeptic5 Juni 2015

Preserving History at Cyark

Elizabeth Lee from CyArk joins us in this episode to share stories of the work done capturing important historical sites digitally. CyArk is a non-profit focused on using technology to preserve the world's important historic and cultural locations digitally. CyArk's founder Ben Kacyra, a pioneer in 3D capture technology, and his wife, founded CyArk after seeing the need to preserve important artifacts and locations digitally before they are lost to natural disasters, human destruction, or the passage of time. We discuss their technology, data, and site selection including the upcoming themes of locations and the CyArk 500.

Elizabeth puts out the call to all listeners to share their opinions on what important sites should be included in The Cyark 500 Challenge - an effort to digitally preserve 500 of the most culturally important heritage sites within the next five years. You can Nominate a site by submitting a short form at CyArk.org

Visit http://www.cyark.org/projects/ to view an immersive, interactive experience of many of the sites preserved.

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Long Term Time Series Forecasting

Long Term Time Series Forecasting

Alex Mallen, Computer Science student at the University of Washington, and Henning Lange, a Postdoctoral Scholar in Applied Math at the University of Washington, join us today to share their work "Deep Probabilistic Koopman: Long-term Time-Series Forecasting Under Periodic Uncertainties."

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Fast and Frugal Time Series Forecasting

Fast and Frugal Time Series Forecasting

Fotios Petropoulos, Professor of Management Science at the University of Bath in The U.K., joins us today to talk about his work "Fast and Frugal Time Series Forecasting."

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Causal Inference in Educational Systems

Causal Inference in Educational Systems

Manie Tadayon, a PhD graduate from the ECE department at University of California, Los Angeles, joins us today to talk about his work "Comparative Analysis of the Hidden Markov Model and LSTM: A Simulative Approach."

11 Okt 202141min

Boosted Embeddings for Time Series

Boosted Embeddings for Time Series

Sankeerth Rao Karingula, ML Researcher at Palo Alto Networks, joins us today to talk about his work "Boosted Embeddings for Time Series Forecasting." Works Mentioned Boosted Embeddings for Time Series Forecasting by Sankeerth Rao Karingula, Nandini Ramanan, Rasool Tahmasbi, Mehrnaz Amjadi, Deokwoo Jung, Ricky Si, Charanraj Thimmisetty, Luisa Polania Cabrera, Marjorie Sayer, Claudionor Nunes Coelho Jr https://www.linkedin.com/in/sankeerthrao/ https://twitter.com/sankeerthrao3 https://lod2021.icas.cc/

4 Okt 202128min

Change Point Detection in Continuous Integration Systems

Change Point Detection in Continuous Integration Systems

David Daly, Performance Engineer at MongoDB, joins us today to discuss "The Use of Change Point Detection to Identify Software Performance Regressions in a Continuous Integration System". Works Mentioned The Use of Change Point Detection to Identify Software Performance Regressions in a Continuous Integration System by David Daly, William Brown, Henrik Ingo, Jim O'Leary, David BradfordSocial Media David's Website David's Twitter Mongodb

27 Sep 202133min

Applying k-Nearest Neighbors to Time Series

Applying k-Nearest Neighbors to Time Series

Samya Tajmouati, a PhD student in Data Science at the University of Science of Kenitra, Morocco, joins us today to discuss her work Applying K-Nearest Neighbors to Time Series Forecasting: Two New Approaches.

20 Sep 202124min

Ultra Long Time Series

Ultra Long Time Series

Dr. Feng Li, (@f3ngli) is an Associate Professor of Statistics in the School of Statistics and Mathematics at Central University of Finance and Economics in Beijing, China. He joins us today to discuss his work Distributed ARIMA Models for Ultra-long Time Series.

13 Sep 202128min

MiniRocket

MiniRocket

Angus Dempster, PhD Student at Monash University in Australia, comes on today to talk about MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification, a fast deterministic transform for time series classification. MINIROCKET reformulates ROCKET, gaining a 75x improvement on larger datasets with essentially the same performance. In this episode, we talk about the insights that realized this speedup as well as use cases.

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