← Authors

Jan Gasthaus

16 papers · 2008–2022 · 6 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (14) 🌍 Conference Polyglot (6) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (13) πŸ—ΊοΈ Taxonomy Completionist (10) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🀝 Dynamic Duo (10) πŸ† Keyword Champion (2) 🌱 Topic Pioneer πŸ”₯ Unstoppable (5) πŸ“ˆ Trend Setter ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (73) πŸ’Ž Century Club (16)

Conferences

NIPS (8) AISTATS (3) ICML (2) ICLR (1) IJCAI (1) JMLR (1)

Top co-authors

Tim Januschowski (10) Yuyang Wang (5) Syama Sundar Rangapuram (4) Valentin Flunkert (4) Konstantinos Benidis (4) David Salinas (3) Michael Bohlke-Schneider (3) Francois-Xavier Aubet (3) Ali Caner Turkmen (2) Kelvin Kan (2)

Keywords

time series forecasting (5) probabilistic forecasting (4) recurrent neural network (3) time series (3) quantile regression (3) bayesian nonparametrics (2) bayesian inference (2) probabilistic forecast (2) neural network (2) anomaly detection (2) probabilistic model (2) probabilistic modeling (2) deep learning (2) quantile crossing (2) covariance estimation (1) language modeling (1) statistical inference (1) online clustering (1) sequence modeling (1) transfer learning (1)

Papers

Multivariate Quantile Function Forecaster AISTATS 2022
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series ICLR 2022
Neural Contextual Anomaly Detection for Time Series IJCAI 2022
On the detrimental effect of invariances in the likelihood for variational inference NIPS 2022
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting AISTATS 2022
Probabilistic Forecasting: A Level-Set Approach NIPS 2021
Detecting Anomalous Event Sequences with Temporal Point Processes NIPS 2021
End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series ICML 2021
GluonTS: Probabilistic and Neural Time Series Modeling in Python JMLR 2020
Deep Rao-Blackwellised Particle Filters for Time Series Forecasting NIPS 2020
Probabilistic Forecasting with Spline Quantile Function RNNs AISTATS 2019
High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes NIPS 2019
Deep Factors for Forecasting ICML 2019
Deep State Space Models for Time Series Forecasting NIPS 2018
Improvements to the Sequence Memoizer NIPS 2010
Dependent Dirichlet Process Spike Sorting NIPS 2008