Publications related to Self-supervised learning

Kernel Methods and Similarity Learning Applied in Computational Chemistry

Over the last two decades, data-powered machine learning (ML) tools have profoundly transformed numerous scientific fields. In computational chemistry, machine learning applications have permitted faster predictions of chemical properties and provided powe ...

EPFL2022

Self-supervised Segmentation via Background Inpainting

Pascal Fua, Mathieu Salzmann, Isinsu Katircioglu, Helge Jochen Rhodin, Victor Constantin

While supervised object detection and segmentation methods achieve impressive accuracy, they generalize poorly to images whose appearance significantly differs from the data they have been trained on. To address this when annotating data is prohibitively e ...

2022

Simultaneous Prediction of Wrist and Hand Motions via Wearable Ultrasound Sensing for Natural Control of Hand Prostheses

Xingchen Yang

Simultaneous prediction of wrist and hand motions is essential for the natural interaction with hand prostheses. In this paper, we propose a novel multi-out Gaussian process (MOGP) model and a multi-task deep learning (MTDL) algorithm to achieve simultaneo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Protein language models trained on multiple sequence alignments learn phylogenetic relationships

Anne-Florence Raphaëlle Bitbol, Damiano Sgarbossa, Umberto Lupo

Self-supervised neural language models with attention have recently been applied to biological sequence data, advancing structure, function and mutational effect prediction. Some protein language models, including MSA Transformer and AlphaFold's EvoFormer, ...

NATURE PORTFOLIO2022

Masked Training of Neural Networks with Partial Gradients

Martin Jaggi, Sebastian Urban Stich, Amirkeivan Mohtashami

State-of-the-art training algorithms for deep learning models are based on stochastic gradient descent (SGD). Recently, many variations have been explored: perturbing parameters for better accuracy (such as in Extra-gradient), limiting SGD updates to a sub ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022

Evolutionary Clustering of Apprentices' Self- Regulated Learning Behavior in Learning Journals

Paola Mejia Domenzain, Christian Giang, Mirko Marras

Learning journals are increasingly used in vocational education to foster self-regulated learning and reflective learning practices. However, for many apprentices, documenting working experiences is a difficult task. In this paper, we profile apprentices' ...

2022

M2D2: Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities

David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, Anthony Hitchcock Thomas

Recent years have seen growing interest in leveraging deep learning models for monitoring epilepsy patients based on electroencephalographic (EEG) signals. However, these approaches often exhibit poor generalization when applied outside of the setting in w ...

2022

How Does Pre-Trained Wav2Vec 2.0 Perform On Domain-Shifted Asr? An Extensive Benchmark On Air Traffic Control Communications

Petr Motlicek, Juan Pablo Zuluaga Gomez, Amrutha Prasad

Recent work on self-supervised pre-training focus on leveraging large-scale unlabeled speech data to build robust end-to-end (E2E) acoustic models (AM) that can be later fine-tuned on downstream tasks e.g., automatic speech recognition (ASR). Yet, few work ...

IEEE2022

On combining denoising with learning-based image decoding

Touradj Ebrahimi, Michela Testolina

Noise is an intrinsic part of any sensor and is present, in various degrees, in any content that has been captured in real life environments. In imaging applications, several pre- and post-processing solutions have been proposed to cope with noise in captu ...

SPIE2022

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Self-supervised learning

Kernel Methods and Similarity Learning Applied in Computational Chemistry

Self-supervised Segmentation via Background Inpainting

Simultaneous Prediction of Wrist and Hand Motions via Wearable Ultrasound Sensing for Natural Control of Hand Prostheses

Personalized Productive Engagement Recognition in Robot-Mediated Collaborative Learning

Protein language models trained on multiple sequence alignments learn phylogenetic relationships

Masked Training of Neural Networks with Partial Gradients

Evolutionary Clustering of Apprentices' Self- Regulated Learning Behavior in Learning Journals

M2D2: Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities

How Does Pre-Trained Wav2Vec 2.0 Perform On Domain-Shifted Asr? An Extensive Benchmark On Air Traffic Control Communications

On combining denoising with learning-based image decoding

Graph Chatbot

Chat with Graph Search

Kernel Methods and Similarity Learning Applied in Computational Chemistry

Masked Training of Neural Networks with Partial Gradients

M2D2: Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities

On combining denoising with learning-based image decoding

Self-supervised Segmentation via Background Inpainting

Personalized Productive Engagement Recognition in Robot-Mediated Collaborative Learning

Simultaneous Prediction of Wrist and Hand Motions via Wearable Ultrasound Sensing for Natural Control of Hand Prostheses

Protein language models trained on multiple sequence alignments learn phylogenetic relationships

Evolutionary Clustering of Apprentices' Self- Regulated Learning Behavior in Learning Journals

How Does Pre-Trained Wav2Vec 2.0 Perform On Domain-Shifted Asr? An Extensive Benchmark On Air Traffic Control Communications