Jan N. van Rijn - Publications, H-index & Citations

Jan N. van Rijn

leiden university - excl lumc

22H指数

106论文数

2.7K被引数

收录论文 16

发表时间

Quantifying Model Uncertainty with AutoML and Rashomon Partial Dependence Profiles: Enabling Trustworthy and Human-centered XAI 使用AutoML和拉什莫恩部分依赖剖面量化模型不确定性：实现可信赖和以人为中心的XAI

Information Systems Frontiers

IF8.3

2026-02-09

OAAI

Mustafa Cavus; Jan N. van Rijn; Przemysław Biecek

Robustness Margin: A New Measure for the Robustness of Neural Networks 鲁棒性裕度：衡量神经网络鲁棒性的新指标

AI VERIFICATION, SAIV 2025

IF0

2026-01-01

PREAI

Kielhoefer, Lionel; Bosman, Annelot W.; Hoos, Holger H.; van Rijn, Jan N.

OpenML: Insights from 10 years and more than a thousand papers OpenML：十年来的洞见与一千多篇论文的成果

Patterns

IF7.4

2025-07-03

OAAI

Bernd Bischl; Giuseppe Casalicchio; Taniya Das; Matthias Feurer; Sebastian Fischer; Pieter Gijsbers; Subhaditya Mukherjee; Andreas C. Müller; László Németh; Luis Oala; Lennart Purucker; Sahithya Ravi; Jan N. van Rijn; Prabhant Singh; Joaquin Vanschoren; Jos van der Velde; Marcel Wever

Artificial Intelligence to Advance Earth Observation: A review of models, recent trends, and pathways forward 人工智能推进地球观测: 模型、近期趋势和前进道路综述

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

IF16.4

2025-01-01

PREAI

Tuia, Devis; Schindler, Konrad; Demir, Beguem; Zhu, Xiao Xiang; Kochupillai, Mrinalini; Dzeroski, Saso; van Rijn, Jan N.; Hoos, Holger H.; Del Frate, Fabio; Datcu, Mihai; Markl, Volker; Le Saux, Bertrand; Schneider, Rochelle; Camps-Valls, Gustau

Learning curves for decision making in supervised machine learning: a survey

MACHINE LEARNING

IF2.9

2024-12-23

OAAI

Mohr, Felix; van Rijn, Jan N.

Understanding transfer learning and gradient-based meta-learning techniques 理解迁移学习和基于梯度的元学习技术

MACHINE LEARNING

IF2.9

2023-12-12

OAAI

Huisman, Mike; Plaat, Aske; van Rijn, Jan N.

Subspace Adaptation Prior for Few-Shot Learning 少镜头学习的子空间适应先验

MACHINE LEARNING

IF2.9

2023-09-19

OAAI

Huisman, Mike; Plaat, Aske; van Rijn, Jan N.

Are LSTMs good few-shot learners?LSTMs是好的少打学习者吗？

MACHINE LEARNING

IF2.9

2023-09-07

OAAI

Huisman, Mike; Moerland, Thomas M.; Plaat, Aske; van Rijn, Jan N.

Hyperparameter importance and optimization of quantum neural networks across small datasets 跨小数据集的量子神经网络的超参数重要性和优化

MACHINE LEARNING

IF2.9

2023-08-31

OAAI

Moussa, Charles; Patel, Yash J.; Dunjko, Vedran; Baeck, Thomas; van Rijn, Jan N.

The Bigger Fish: A Comparison of Meta-Learning QSAR Models on Low-Resourced Aquatic Toxicity Regression Tasks

ENVIRONMENTAL SCIENCE & TECHNOLOGY

IF11.3

2023-06-14

OAAI

Schlender, Thalea; Viljanen, Markus; van Rijn, Jan N.; Mohr, Felix; Peijnenburg, Willie J. G. M.; Hoos, Holger H.; Rorije, Emiel; Wong, Albert

Speeding up neural network robustness verification via algorithm configuration and an optimised mixed integer linear programming solver portfolio

MACHINE LEARNING

IF2.9

2022-09-08

OAAI

Konig, Matthias; Hoos, Holger H.; van Rijn, Jan N.

Stateless neural meta-learning using second-order gradients

MACHINE LEARNING

IF2.9

2022-07-13

OAAI

Huisman, Mike; Plaat, Aske; van Rijn, Jan N.

Multi-task learning with a natural metric for quantitative structure activity relationship learning

JOURNAL OF CHEMINFORMATICS

IF5.7

2019-11-12

OAAI

Sadawi, Noureddin; Olier, Ivan; Vanschoren, Joaquin; van Rijn, Jan N.; Besnard, Jeremy; Bickerton, Richard; Grosan, Crina; Soldatova, Larisa; King, Ross D.

The algorithm selection competitions 2015 and 2017

artificial intelligence review

IF4.6

2019-07-01

OAAI

Lindauer, Marius; van Rijn, Jan N.; Kotthoff, Lars

The online performance estimation framework: heterogeneous ensemble learning for data streams

MACHINE LEARNING

IF2.9

2017-12-21

OAAI

van Rijn, Jan N.; Holmes, Geoffrey; Pfahringer, Bernhard; Vanschoren, Joaquin