Januschowski, Tim

1. Neural Flows: Efficient Alternative to Neural ODEs
   2021/10/25 by Marin Biloš, Biloš, Marin, Johanna Sommer +7 · 16 citations
   Computer Science · Decision Sciences · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications #Numerical Analysis (math.NA) #Stock Market Forecasting Methods
2. Neural Temporal Point Processes: A Review
   2021/04/08 by Shchur, Oleksandr, Türkmen, Ali Caner, Januschowski, Tim +1 · 12 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG)
3. GluonTS: Probabilistic Time Series Models in Python
   2019/06/12 by A. Alexandrov, Alexandrov, Alexander, Konstantinos Benidis +23 · 12 citations
   Computer Science · Decision Sciences · #Time Series Analysis and Forecasting #Computational Physics and Python Applications #Stock Market Forecasting Methods
4. Criteria for Classifying Forecasting Methods
   2022/12/07 by Januschowski, Tim, Gasthaus, Jan, Wang, Yuyang +4 · 6 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
5. The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models
   2020/05/20 by Rabanser, Stephan, Januschowski, Tim, Flunkert, Valentin +2 · 4 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
6. Multivariate Quantile Function Forecaster
   2022/02/23 by Kan, Kelvin, Aubet, François-Xavier, Januschowski, Tim +4 · 3 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
7. Online false discovery rate control for anomaly detection in time series
   2021/12/06 by Quentin Rebjock, Barış Kurt, Rebjock, Quentin +5 · 2 citations
   Computer Science · #Anomaly Detection Techniques and Applications #Data Stream Mining Techniques #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST) #Time Series Analysis and Forecasting
8. Deep Learning based Forecasting: a case study from the online fashion industry
   2023/05/23 by Manuel Kunz, Kunz, Manuel, Stefan Birr +31 · 1 voice · 1 citation
   Decision Sciences · #Advanced Statistical Process Monitoring #Forecasting Techniques and Applications #cs.AI #cs.LG
9. A simple and effective predictive resource scaling heuristic for large-scale cloud applications
   2020/08/03 by Flunkert, Valentin, Rebjock, Quentin, Castellon, Joel +2 · 1 citation
   #Distributed #FOS: Computer and information sciences #Machine Learning (stat.ML) #Parallel #and Cluster Computing (cs.DC)
10. Intermittent Demand Forecasting with Deep Renewal Processes
    2019/11/23 by Turkmen, Ali Caner, Wang, Yuyang, Januschowski, Tim · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
11. Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models
    2020/07/30 by Ayed, Fadhel, Stella, Lorenzo, Januschowski, Tim +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
12. Deep Explicit Duration Switching Models for Time Series
    2021/10/26 by Abdul Fatir Ansari, Konstantinos Benidis, Ansari, Abdul Fatir +13 · 1 citation
    Computer Science · Economics, Econometrics and Finance · #Time Series Analysis and Forecasting #Complex Systems and Time Series Analysis #Neural Networks and Applications
13. Diverse Counterfactual Explanations for Anomaly Detection in Time Series
    2022/03/21 by Déborah Sulem, Michele Donini, Sulem, Deborah +15 · 1 citation
    Computer Science · #Anomaly Detection Techniques and Applications #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Time Series Analysis and Forecasting
14. Multivariate Time Series Forecasting with Latent Graph Inference
    2022/03/07 by Satorras, Victor Garcia, Rangapuram, Syama Sundar, Januschowski, Tim · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
15. Tricks from the Trade for Large-Scale Markdown Pricing: Heuristic Cut Generation for Lagrangian Decomposition
    2024/04/03 by Robert Streeck, Torsten Gellert, Streeck, Robert +11 · 1 citation
    Business, Management and Accounting · Economics, Econometrics and Finance · #Consumer Market Behavior and Pricing #Diverse Scientific and Economic Studies #European Monetary and Fiscal Policies #FOS: Mathematics #Optimization and Control (math.OC)
16. On the detrimental effect of invariances in the likelihood for variational inference
    2022/09/15 by Richard Kurle, Ralf Herbrich, Kurle, Richard +7 · 1 citation
    Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning and Algorithms