Conditional Probability Estimation

An online journal club on the topics Conditional Probability Estimation. Our cover topics on all sorts of probabilistic approach, such as VAE, normalizing, graph neural network, probabilistic time series forecasting.

Introduction: Conditional Probability Estimation

³⁶ Evaluating time series forecasting models

Published: 2022-06-10

Tags:

#Time series #Machine Learning #Bayesian

References: - Cerqueira V, Torgo L, Mozetic I. Evaluating time series forecasting models: An empirical study on performance estimation methods. arXiv [cs.LG]. 2019. Available: http://arxiv.org/abs/1905.11744

Summary: Our topic for this session is Cerqueira V, Torgo L, Mozetic I. Evaluating time series forecasting models: An empirical study on performance estimation methods. arXiv [cs.LG]. 2019. Available: http://arxiv.org/abs/1905.11744 Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.

Pages: 60

³² Conformal Time Series Forecasting

Published: 2022-03-10

Tags:

#Machine Learning #Time Series

References: - Lim B, Zohren S. Time Series Forecasting With Deep Learning: A Survey. arXiv [stat.ML]. 2020. Available: http://arxiv.org/abs/2004.13408 - Gneiting T, Katzfuss M. Probabilistic Forecasting. Annu Rev Stat Appl. 2014;1: 125–151. doi:10.1146/annurev-statistics-062713-085831

Summary: We start our new journey on time series by sharing and discussing two review papers: Lim B, Zohren S. Time Series Forecasting With Deep Learning: A Survey. arXiv [stat.ML]. 2020. Available: http://arxiv.org/abs/2004.13408 Gneiting T, Katzfuss M. Probabilistic Forecasting. Annu Rev Stat Appl. 2014;1: 125–151. doi:10.1146/annurev-statistics-062713-085831 (pdf) Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.

Pages: 60

³² Review of Time Series Forecasting

Published: 2022-04-12

Tags:

#Machine Learning #Time Series

Summary: Lim B, Zohren S. Time Series Forecasting With Deep Learning: A Survey. arXiv [stat.ML]. 2020. Available: http://arxiv.org/abs/2004.13408 Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.

Pages: 60

³² Counterfactual Explanation in Multivariate Time Series

Published: 2022-04-12

Tags:

#Machine Learning #Time Series #Counterfactual

References: - Ates E, Aksar B, Leung VJ, Coskun AK. Counterfactual Explanations for Machine Learning on Multivariate Time Series Data. arXiv [cs.LG]. 2020. Available: http://arxiv.org/abs/2008.10781

Summary: Ates E, Aksar B, Leung VJ, Coskun AK. Counterfactual Explanations for Machine Learning on Multivariate Time Series Data. arXiv [cs.LG]. 2020. Available: http://arxiv.org/abs/2008.10781 Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.

Pages: 60

³² Causal Inference

Published: 2022-05-09

Tags:

#Machine Learning #Time Series #Counterfactual

Summary: Alexa will lead a discussion on causal inference. Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.

Pages: 60

³¹ Uncertainty in Deep Learning

Published: 2022-02-26

Tags:

#Machine Learning #Bayesian #Uncertainty

Summary: Topic: uncertainty in deep learning References: Gawlikowski, J. et al. A Survey of Uncertainty in Deep Neural Networks. Arxiv (2021). Jospin, L. V., Buntine, W., Boussaid, F., Laga, H. & Bennamoun, M. Hands-on Bayesian Neural Networks – a Tutorial for Deep Learning Users. Arxiv (2020). Gal, Yarin. “Uncertainty in deep learning.” (2016): 3. Use the following timezone tool or click on the “Add to Calendar” button on the sidebar.

Pages: 60