activity
20232026
most citedLearning-based adaption of robotic friction models

17 citations · 19 across the 11 of their papers we have counts for

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Showing cs.LGShow all

5 papers · 1 filter

cs.LG2026

Exact Quantile Balancing and Load-Error Injection for Mixture-of-Experts

Pit Neitemeier, Jiaze Li, Alessio Serra +2

Mixture-of-Experts (MoE) training requires global load balance to prevent expert under-utilization and local balance for efficient expert-parallel execution. Existing distributed Q…

cs.LG2025

Improved probabilistic regression using diffusion models

Carlo Kneissl, Christopher Bülte, Philipp Scholl +1

Probabilistic regression models the entire predictive distribution of a response variable, offering richer insights than classical point estimates and directly allowing for uncerta…

cs.LG2025

Graph Neural Networks for Enhancing Ensemble Forecasts of Extreme Rainfall

Christopher Bülte, Sohir Maskey, Philipp Scholl +2

Climate change is increasing the occurrence of extreme precipitation events, threatening infrastructure, agriculture, and public safety. Ensemble prediction systems provide probabi…

cs.LG2025★ 1 cited

Probabilistic neural operators for functional uncertainty quantification

Christopher Bülte, Philipp Scholl, Gitta Kutyniok

Neural operators aim to approximate the solution operator of a system of differential equations purely from data. They have shown immense success in modeling complex dynamical syst…

cs.LG2024

Robust identifiability for symbolic recovery of differential equations

Hillary Hauger, Philipp Scholl, Gitta Kutyniok

Recent advancements in machine learning have transformed the discovery of physical laws, moving from manual derivation to data-driven methods that simultaneously learn both the str…