Nicolas Pielawski

Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models

Arteaga, Gabriel Y.; Schön, Thomas B.; Pielawski, Nicolas

Ingår i Proceedings of the 6th Northern Lights Deep Learning Conference (NLDL), s. 1-15, 2025

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TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data

Pielawski, Nicolas; Andersson, Axel; Avenel, Christophe; Beháňová, Andrea et al.

Ingår i Heliyon, 2023

• DOI för TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data
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Learning-based prediction, representation, and multimodal registration for bioimage processing

Pielawski, Nicolas

2023

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Rotationally Equivariant Representation Learning for Multimodal Images

Wetzer, Elisabeth; Pielawski, Nicolas; Öfverstedt, Johan; Lu, Jiahao et al.

2022

Contrastive Learning for Equivariant Multimodal Image Representations

Wetzer, Elisabeth; Pielawski, Nicolas; Breznik, Eva; Öfverstedt, Johan et al.

2021

TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data

Pielawski, Nicolas; Andersson, Axel; Avenel, Christophe; Beháňová, Andrea et al.

Ingår i Heliyon, 2023

• DOI för TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data
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Introducing Hann windows for reducing edge-effects in patch-based image segmentation

Pielawski, Nicolas; Wählby, Carolina

Ingår i PLOS ONE, 2020

• DOI för Introducing Hann windows for reducing edge-effects in patch-based image segmentation
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Deep Learning in Image Cytometry: A Review

Gupta, Anindya; Harrison, Philip J.; Wieslander, Håkan; Pielawski, Nicolas et al.

Ingår i Cytometry Part A, s. 366-380, 2019

• DOI för Deep Learning in Image Cytometry: A Review
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Learning-based prediction, representation, and multimodal registration for bioimage processing

Pielawski, Nicolas

2023

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Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models

Arteaga, Gabriel Y.; Schön, Thomas B.; Pielawski, Nicolas

Ingår i Proceedings of the 6th Northern Lights Deep Learning Conference (NLDL), s. 1-15, 2025

• Ladda ner fulltext (pdf) av Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models

Rotationally Equivariant Representation Learning for Multimodal Images

Wetzer, Elisabeth; Pielawski, Nicolas; Öfverstedt, Johan; Lu, Jiahao et al.

2022

Contrastive Learning for Equivariant Multimodal Image Representations

Wetzer, Elisabeth; Pielawski, Nicolas; Breznik, Eva; Öfverstedt, Johan et al.

2021

Registration of Multimodal Microscopy Images using CoMIR – learned structural image representations

Wetzer, Elisabeth; Pielawski, Nicolas; Öfverstedt, Johan; Lu, Jiahao et al.

2021

Comir: Contrastive multimodal image representation for registration

Wetzer, Elisabeth; Pielawski, Nicolas; Öfverstedt, Johan; Lu, Jiahao et al.

2021

CoMIR: Contrastive Multimodal Image Representation for Registration

Pielawski, Nicolas; Wetzer, Elisabeth; Öfverstedt, Johan; Lu, Jiahao et al.

Ingår i NeurIPS - 34th Conference on Neural Information Processing Systems, 2020

Cross-modal Representation Learning for Efficient Registration of Multiphoton and Brightfield Microscopy Images of Skin Tissue

Wetzer, Elisabeth; Pielawski, Nicolas; Öfverstedt, Johan; Jiahao, Lu et al.

Ingår i 4th NEUBIAS Conference, Bordeaux, France, 2020

In Silico Prediction of Cell Traction Forces

Pielawski, Nicolas; Hu, Jianjiang; Strömblad, Staffan; Wählby, Carolina

Ingår i 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), s. 877-881, 2020

• DOI för In Silico Prediction of Cell Traction Forces

TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data

Pielawski, Nicolas; Andersson, Axel; Avenel, Christophe; Behanova, Andrea et al.

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Global Parameter Optimization for Multimodal Biomedical Image Registration

Pielawski, Nicolas; Öfverstedt, Johan; Wetzer, Elisabeth