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OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis

Related publications (63)

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HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration

David Atienza Alonso, Tomas Teijeiro Campo, William Andrew Simon, Una Pale

The HyperDimensional Computing (HDC) Machine Learning (ML) paradigm is highly interesting for applications involving continuous, semi-supervised learning for long-term monitoring. However, its accuracy is not yet on par with other ML approaches, necessitat ...

Association for Computing MachineryNew YorkNYUnited States2022

Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis

Pascal Fua, Jiancheng Yang, Pamuditha Udaranga Wickramasinghe, Rui Shi

The human annotations are imperfect, especially when produced by junior practitioners. Multi-expert consensus is usually regarded as golden standard, while this annotation protocol is too expensive to implement in many real-world projects. In this study, w ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Detecting Text Reuse with Passim

Matteo Romanello

In this lesson you will learn about text reuse detection – the automatic identification of reused passages in texts – and why you might want to use it in your research. Through a detailed installation guide and two case studies, this lesson will teach you ...

2021

Evaluating earthquake-induced losses, such as structural repair costs, downtime and casualties, is becoming a standard practice within the performance-based earthquake engineering framework. Nonetheless, this evaluation is a demanding task that requires de ...

2021

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We propose and evaluate a secure-multiparty-computation (MPC) solution in the semi-honest model with dishonest majority that is based on multiparty homomorphic encryption (MHE). To support our solution, we introduce a multiparty version of the Brakerski-Fa ...

2021

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Byzantine robustness has received significant attention recently given its importance for distributed and federated learning. In spite of this, we identify severe flaws in existing algorithms even when the data across the participants is identically distri ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Common workflows for computing material properties using different quantum engines

Berend Smit, Nicola Marzari, Giovanni Pizzi, Martin Uhrin, Marnik Bercx, Kristjan Eimre, Austin Jacob Zadoks, Samuel Poncé, Aliaksandr Yakutovich, Sebastiaan Philippe Huber, Conrad Johnston, Christopher John Sewell, Gian-Marco Rignanese

The prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods is both a boon ...

2021

The open EEGLAB portal Interface: High-Performance computing with EEGLAB

Fiorenzo Artoni

EEGLAB signal processing environment is currently the leading open-source software for processing electroencephalographic (EEG) data. The Neuroscience Gateway (NSG, nsgportal.org) is a web and API-based portal allowing users to easily run a variety of neur ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2021

We present an analysis of the SwissCovid application which is currently being tested. We observe that the essential part of SwissCovid is under the control of Apple and Google. Outsourcing the heart of SwissCovid to Apple and Google has apparent benefits i ...

2020

An automated calibration framework and open source tools for 3D lake hydrodynamic models

Alfred Johny Wüest, Damien Bouffard, Andrea Cimatoribus, Theo Baracchini

Understanding lake dynamics is crucial to provide scientifically credible information for ecosystem management. In this context, three-dimensional hydrodynamic models are a key information source to assess critical but often subtle changes in lake dynamics ...

2020