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Development funds are essential to finance climate change adaptation and are thus an important part of international climate policy. % However, the absence of a common reporting practice makes it difficult to assess the amount and…

Computers and Society · Computer Science 2022-12-01 Janos Borst , Thomas Wencker , Andreas Niekler

A central task in analyzing complex dynamics is to determine the loci of information storage and the communication topology of information flows within a system. Over the last decade and a half, diagnostics for the latter have come to be…

Statistical Mechanics · Physics 2016-06-20 Ryan G. James , Nix Barnett , James P. Crutchfield

Domain gaps are among the most relevant roadblocks in the clinical translation of machine learning (ML)-based solutions for medical image analysis. While current research focuses on new training paradigms and network architectures, little…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Patrick Godau , Piotr Kalinowski , Evangelia Christodoulou , Annika Reinke , Minu Tizabi , Luciana Ferrer , Paul Jäger , Lena Maier-Hein

Datasets used in immunotherapy response prediction are typically small in size, as well as diverse in cancer type, drug administered, and sequencer used. Models often drop in performance when tested on patient cohorts that are not included…

Machine Learning · Computer Science 2026-04-02 Sayed Hashim , Frank Soboczenski , Paul Cairns

The replicability crisis has drawn attention to numerous weaknesses in psychology and social science research practice. In this work we focus on three issues that cannot be addressed with replication alone, and which deserve more attention:…

Applications · Statistics 2021-07-16 Matthew J. Vowels

Unmeasured confounders are a major source of bias in regression-based effect estimation and causal inference. In this paper, we advocate a new profiled transfer learning framework, ProTrans, to address confounding effects in the target…

Methodology · Statistics 2025-09-04 Ziyuan Chen , Yifan Jiang , Jingyuan Liu , Fang Yao

In real-world clinical settings, magnetic resonance imaging (MRI) frequently suffers from missing modalities due to equipment variability or patient cooperation issues, which can significantly affect model performance. To address this…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Zhejia Zhang , Junjie Wang , Le Zhang

Many scientific datasets are compositional in nature. Important biological examples include species abundances in ecology, cell-type compositions derived from single-cell sequencing data, and amplicon abundance data in microbiome research.…

Machine Learning · Computer Science 2024-05-29 Elisabeth Ailer , Christian L. Müller , Niki Kilbertus

Transfer learning enhances prediction accuracy on a target distribution by leveraging data from a source distribution, demonstrating significant benefits in various applications. This paper introduces a novel dissimilarity measure that…

Machine Learning · Statistics 2024-12-12 Mitsuhiro Fujikawa , Yohei Akimoto , Jun Sakuma , Kazuto Fukuchi

When dealing with control systems, it is useful and even necessary to assess the performance of underlying transfer functions. The functions may or may not be linear, may or may not be even monotonic. In addition, they may have structural…

Statistics Theory · Mathematics 2018-06-28 Nadezhda Gribkova , Ričardas Zitikis

Clinical and biomedical research in low-resource settings often faces significant challenges due to the need for high-quality data with sufficient sample sizes to construct effective models. These constraints hinder robust model training…

Transfer Optimization has gained a remarkable attention from the Swarm and Evolutionary Computation community in the recent years. It is undeniable that the concepts underlying Transfer Optimization are formulated on solid grounds. However,…

Neural and Evolutionary Computing · Computer Science 2022-11-14 Eneko Osaba , Javier Del Ser , Ponnuthurai N. Suganthan

Important questions for impact evaluation require knowledge not only of average effects, but of the distribution of treatment effects. The inability to observe individual counterfactuals makes answering these empirical questions…

Econometrics · Economics 2026-05-25 Bruno Fava

Empirical work often uses treatment assigned following geographic boundaries. When the effects of treatment cross over borders, classical difference-in-differences estimation produces biased estimates for the average treatment effect. In…

Econometrics · Economics 2023-06-13 Kyle Butts

This paper shows that standard assessment methodology for style transfer has several significant problems. First, the standard metrics for style accuracy and semantics preservation vary significantly on different re-runs. Therefore one has…

Computation and Language · Computer Science 2022-11-15 Alexey Tikhonov , Viacheslav Shibaev , Aleksander Nagaev , Aigul Nugmanova , Ivan P. Yamshchikov

High throughput metabolomics data are fraught with both non-ignorable missing observations and unobserved factors that influence a metabolite's measured concentration, and it is well known that ignoring either of these complications can…

Methodology · Statistics 2019-09-09 Chris McKennan , Carole Ober , Dan Nicolae

The present study investigates the performance of several statistical tests to detect publication bias in diagnostic meta-analysis by means of simulation. While bivariate models should be used to pool data from primary studies in diagnostic…

Methodology · Statistics 2022-11-24 Paul-Christian Bürkner , Philipp Doebler

In the note an error in Low and Lapsley's article ("Optimization Flow Control, I: Basic Algorithm and Convergence", IEEE/ACM Transactions on Networking, 7(6), pp. 861-874, 1999) is pointed out. Because of this error the proof of the Theorem…

Networking and Internet Architecture · Computer Science 2016-10-11 Andrzej Karbowski

Recent multi-omic microbiome studies enable integrative analysis of microbes and metabolites, uncovering their associations with various host conditions. Such analyses require multivariate models capable of accounting for the complex…

The Brier score is a widely used metric evaluating overall performance of probabilistic predictions for binary outcomes in clinical research. However, its interpretation can be complex, as it does not align with commonly taught concepts in…

Applications · Statistics 2025-07-08 Linard Hoessly