Planetizen

AI promises to finally make public engagement meaningful. We put it to the test.

Everything you need to know about how we analyzed the 13,000+ comments submitted in the federal government’s request for ...
IEEE

DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series

Abstract: In time series anomaly detection (TSAD), the scarcity of labeled data poses a challenge to the development of accurate models. Unsupervised domain adaptation (UDA) offers a solution by ...
Unite.AI

Jeremy Freeman, Co-Founder and CTO of Allstacks – Interview Series

Jeremy Freeman, Co-Founder and CTO of Allstacks, is a software engineer, technology architect, and entrepreneur with a career ...
GitHub

Toto - Time Series Optimized Transformer for Observability

Toto is a foundation model for multivariate time series forecasting with a focus on observability metrics. Toto 2.0 is the current recommended release, featuring a family of u-μP-scaled models ranging ...
IEEE

Optimized Time Series Feature Selection for Manufacturing AI: Reducing Complexity and Improving Classification Accuracy

Abstract: Although AI enhances productivity and quality in manufacturing, real-time validation remains difficult due to the complexity and high-dimensionality of time series data under strict ...
GitHub

Tigramite – Causal inference for time series datasets

Update: Tigramite now has a new CausalEffects class that allows to estimate (conditional) causal effects and mediation based on assuming a causal graph. Have a look at the tutorial. Further, Tigramite ...