Jan Gasthaus
16 papers · 2008–2022 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (35) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π±
Topic Pioneer
π€
Dynamic Duo
(10)
π
Keyword Champion
π
Trend Setter
π
Century Club Β· Bronze
π₯
Unstoppable Β· Bronze
ποΈ
Keyword Collector
(79)
β‘
Prolific Year Β· Productive
Top co-authors
Research topics
Machine Learning
(15)
Optimization & Theory
(10)
Data Science & Analytics
(9)
Methods
(9)
Core Methods
(8)
Artificial Intelligence
(7)
Deep Learning
(6)
Bayesian & Probabilistic Β· Machine Learning
(6)
Bayesian & Probabilistic Β· Artificial Intelligence
(6)
Learning Types Β· Machine Learning
(6)
Learning Types Β· Deep Learning
(3)
Models
(3)
Architectures
(2)
Healthcare & Medicine
(1)
Natural Language Processing
(1)
Keywords
time series forecasting
(5)
time series
(4)
probabilistic forecasting
(4)
quantile regression
(3)
recurrent neural network
(3)
quantile crossing
(2)
deep learning
(2)
probabilistic forecast
(2)
probabilistic model
(2)
anomaly detection
(2)
bayesian inference
(2)
bayesian nonparametrics
(2)
probabilistic modeling
(2)
state space model
(2)
neural network
(2)
language modeling
(1)
data augmentation
(1)
statistical inference
(1)
online clustering
(1)
sequence modeling
(1)
Papers
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting
AISTATS 2022
Multivariate Quantile Function Forecaster
AISTATS 2022
Neural Contextual Anomaly Detection for Time Series
IJCAI 2022
On the detrimental effect of invariances in the likelihood for variational inference
NeurIPS 2022
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series
ICLR 2022
Detecting Anomalous Event Sequences with Temporal Point Processes
NeurIPS 2021
End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series
ICML 2021
Probabilistic Forecasting: A Level-Set Approach
NeurIPS 2021
Deep Rao-Blackwellised Particle Filters for Time Series Forecasting
NeurIPS 2020
GluonTS: Probabilistic and Neural Time Series Modeling in Python
JMLR 2020
Deep Factors for Forecasting
ICML 2019
High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes
NeurIPS 2019
Probabilistic Forecasting with Spline Quantile Function RNNs
AISTATS 2019
Deep State Space Models for Time Series Forecasting
NeurIPS 2018
Improvements to the Sequence Memoizer
NeurIPS 2010
Dependent Dirichlet Process Spike Sorting
NeurIPS 2008