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

48 End of 2022 Fireside Chat

Published:
Summary: Fireside chat: data statistics machine learning engineering Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60

47 Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting

Published:
Summary: Topic: Rasul K, Seward C, Schuster I, Vollgraf R. Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting. arXiv [cs.LG]. 2021. Available: http://arxiv.org/abs/2101.12072 Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60

46 Diffusion Models: A Comprehensive Survey of Methods and Applications

Published:
Summary: Topic: Yang L, Zhang Z, Song Y, Hong S, Xu R, Zhao Y, et al. Diffusion Models: A Comprehensive Survey of Methods and Applications. arXiv [cs.LG]. 2022. Available: http://arxiv.org/abs/2209.00796 Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60

45 Probabilistic Forecasting: A Level-Set Approach

Published:
Summary: Topic: Hasson H, Wang Y, Januschowski T, Gasthaus J. Probabilistic forecasting: A level-set approach. [cited 25 Jan 2022]. Available: https://assets.amazon.science/a7/2b/29e00a5e429b8f2e708091ecb53e/probabilistic-forecasting-a-level-set-approach.pdf Code: https://github.com/awslabs/gluonts/blob/fcc50e8be222bcf3b3da47ed1ed50b467e03f7e8/src/gluonts/ext/rotbaum/_model.py Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60

44 Forecasting with Trees

Published:
Summary: Topic: Forecasting with Trees References: https://www.sciencedirect.com/science/article/pii/S0169207021001679 Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60

43 Gradient Boosted Decision Trees (II)

Published:
Summary: Topic: XGBoost, LightGBM and Trees (II) References: https://lightgbm.readthedocs.io/en/v3.3.2/ https://papers.nips.cc/paper/2017/hash/6449f44a102fde848669bdd9eb6b76fa-Abstract.html Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60

42 Gradient Boosted Decision Trees (I)

Published:
Summary: Topic: XGBoost, LightGBM and Trees (I) References: https://xgboost.readthedocs.io/en/stable/tutorials/model.html Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60

41 Neural ODE

Published:
Summary: Topic: Chen RTQ, Rubanova Y, Bettencourt J, Duvenaud D. Neural Ordinary Differential Equations. arXiv [cs.LG]. 2018. Available: http://arxiv.org/abs/1806.07366 Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60

40 M Competition

Published:
Summary: We will discuss the M competition. @小紫花: M5: 2020 年的一个比赛，预测沃尔玛在米国 3 个州、 10 个店、3000 多个产品的销售，要求预测 28 天。两个比赛：预测一个中值，或者预测一个分布（9 个数）。今年有 M6 官网，指引 PDF https://mofc.unic.ac.cy/m5-competition/ 中值 https://www.kaggle.com/competitions/m5-forecasting-accuracy/ 分布 https://www.kaggle.com/competitions/m5-forecasting-uncertainty 比赛背景、组织、运营总结 https://www.sciencedirect.com/science/article/pii/S0169207021001187 中值预测总结 https://www.sciencedirect.com/science/article/pii/S0169207021001874 分布预测总结（我比较感兴趣） https://www.sciencedirect.com/science/article/pii/S0169207021001722 一篇评论文章 https://www.sciencedirect.com/science/article/abs/pii/S016920702100128X 对讨论的回复 https://www.sciencedirect.com/science/article/abs/pii/S0169207022000644 Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60

39 Data Augmentation for Time Series

Published:
Summary: Wen Q, Sun L, Yang F, Song X, Gao J, Wang X, et al. Time Series Data Augmentation for Deep Learning: A Survey. arXiv [cs.LG]. 2020. Available: http://arxiv.org/abs/2002.12478 Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60

38 Temporal Fusion Transformer

Published:
Summary: Lim B, Arik SO, Loeff N, Pfister T. Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting. In: arXiv.org [Internet]. 19 Dec 2019 [cited 9 Jul 2022]. Available: https://arxiv.org/abs/1912.09363 Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60

37 DeepAR

Published:
Summary: Topic: DeepAR. Use the following timezone tool or click on the “Add to Calendar” button on the sidebar. Click here for an interactive widget.
Pages: 60