16 citations · 28 across the 10 of their papers we have counts for
10 papers
EMBL AI Librarian: Life-Sciences Knowledge Layer for AI Agents
Luigi Sigillo, Matteo Silvestri, Francesco Tabaro +9
The web is increasingly accessed by AI agents rather than humans. Every agent needs knowledge, especially in the life-sciences, where agentic pipelines are growing fast. Access to…
A Decade in a Systematic Review: The Evolution and Impact of Cell Painting
Srijit Seal, Maria-Anna Trapotsi, Ola Spjuth +5
High-content image-based assays have fueled significant discoveries in the life sciences in the past decade (2013-2023), including novel insights into disease etiology, mechanism o…
Scalable federated machine learning with FEDn
Morgan Ekmefjord, Addi Ait-Mlouk, Sadi Alawadi +5
Federated machine learning has great promise to overcome the input privacy challenge in machine learning. The appearance of several projects capable of simulating federated learnin…
Smart Resource Management for Data Streaming using an Online Bin-packing Strategy
Oliver Stein, Ben Blamey, Johan Karlsson +4
Data stream processing frameworks provide reliable and efficient mechanisms for executing complex workflows over large datasets. A common challenge for the majority of currently av…
Combining Prediction Intervals on Multi-Source Non-Disclosed Regression Datasets
Ola Spjuth, Robin Carrión Brännström, Lars Carlsson +1
Conformal Prediction is a framework that produces prediction intervals based on the output from a machine learning algorithm. In this paper we explore the case when training data i…
Repair and Resource Scheduling in Unbalanced Distribution Systems using Neighborhood Search
Anmar Arif, Zhaoyu Wang, Jianhui Wang +1
This paper proposes an optimization strategy to assist utility operators to recover power distribution systems after large outages. Specifically, a mixed-integer linear programming…
Aggregating Predictions on Multiple Non-disclosed Datasets using Conformal Prediction
Ola Spjuth, Lars Carlsson, Niharika Gauraha
Conformal Prediction is a machine learning methodology that produces valid prediction regions under mild conditions. In this paper, we explore the application of making predictions…
On-Demand Virtual Research Environments using Microservices
Marco Capuccini, Anders Larsson, Matteo Carone +5
The computational demands for scientific applications are continuously increasing. The emergence of cloud computing has enabled on-demand resource allocation. However, relying sole…
conformalClassification: A Conformal Prediction R Package for Classification
Niharika Gauraha, Ola Spjuth
The conformalClassification package implements Transductive Conformal Prediction (TCP) and Inductive Conformal Prediction (ICP) for classification problems. Conformal Prediction (C…
Conformal Prediction in Learning Under Privileged Information Paradigm with Applications in Drug Discovery
Niharika Gauraha, Lars Carlsson, Ola Spjuth
This paper explores conformal prediction in the learning under privileged information (LUPI) paradigm. We use the SVM+ realization of LUPI in an inductive conformal predictor, and…