1 citations · 3 across the 18 of their papers we have counts for
4 papers · 1 filter
Towards Comparable Active Learning
Thorben Werner, Johannes Burchert, Lars Schmidt-Thieme
Active Learning has received significant attention in the field of machine learning for its potential in selecting the most informative samples for labeling, thereby reducing data…
Routing Arena: A Benchmark Suite for Neural Routing Solvers
Daniela Thyssens, Tim Dernedde, Jonas K. Falkner +1
Neural Combinatorial Optimization has been researched actively in the last eight years. Even though many of the proposed Machine Learning based approaches are compared on the same…
Too Big, so Fail? -- Enabling Neural Construction Methods to Solve Large-Scale Routing Problems
Jonas K. Falkner, Lars Schmidt-Thieme
In recent years new deep learning approaches to solve combinatorial optimization problems, in particular NP-hard Vehicle Routing Problems (VRP), have been proposed. The most impact…
Forecasting Irregularly Sampled Time Series using Graphs
Vijaya Krishna Yalavarthi, Kiran Madhusudhanan, Randolf Sholz +5
Forecasting irregularly sampled time series with missing values is a crucial task for numerous real-world applications such as healthcare, astronomy, and climate sciences. State-of…