activity
20122022
most citedGluonTS: Probabilistic Time Series Models in Python

77 citations · 195 across the 12 of their papers we have counts for

collaborators

17 papers

stat.ML20221 cited

Criteria for Classifying Forecasting Methods

Tim Januschowski, Jan Gasthaus, Yuyang Wang +4

Classifying forecasting methods as being either of a "machine learning" or "statistical" nature has become commonplace in parts of the forecasting literature and community, as exem…

cs.LG20222 cited

On the detrimental effect of invariances in the likelihood for variational inference

Richard Kurle, Ralf Herbrich, Tim Januschowski +2

Variational Bayesian posterior inference often requires simplifying approximations such as mean-field parametrisation to ensure tractability. However, prior work has associated the…

math.NA2022

Modeling Advection on Directed Graphs using Matérn Gaussian Processes for Traffic Flow

Danielle C Maddix, Nadim Saad, Yuyang Wang

The transport of traffic flow can be modeled by the advection equation. Finite difference and finite volumes methods have been used to numerically solve this hyperbolic equation on…

cs.LG20212 cited

Correcting Exposure Bias for Link Recommendation

Shantanu Gupta, Hao Wang, Zachary C. Lipton +1

Link prediction methods are frequently applied in recommender systems, e.g., to suggest citations for academic papers or friends in social networks. However, exposure bias can aris…

cs.LG2021

Zero-Shot Recommender Systems

Hao Ding, Yifei Ma, Anoop Deoras +2

Performance of recommender systems (RS) relies heavily on the amount of training data available. This poses a chicken-and-egg problem for early-stage products, whose amount of data…

cs.LG2021

Variance Reduced Training with Stratified Sampling for Forecasting Models

Yucheng Lu, Youngsuk Park, Lifan Chen +3

In large-scale time series forecasting, one often encounters the situation where the temporal patterns of time series, while drifting over time, differ from one another in the same…