Active Learning Method for Virtual Support Vector Machine with self-learning constraints
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Updated
Sep 15, 2024 - R
Active Learning Method for Virtual Support Vector Machine with self-learning constraints
[IJCNN 2021] Node Embedding using Mutual Information and Self-Supervision based Bi-level Aggregation
SemiBin: metagenomics binning with self-supervised deep learning
A curated list of world models for autonomous driving. Keep updated.
[IJCAI-24] Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting
ICASSP 2023-2024 Papers: A complete collection of influential and exciting research papers from the ICASSP 2023-24 conferences. Explore the latest advancements in acoustics, speech and signal processing. Code included. Star the repository to support the advancement of audio and signal processing!
Snuffy: Efficient Whole Slide Image Classifier | ECCV 2024
Open source Python library for building bioimage analysis pipelines
[SLT'24] The official implementation of SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model
A collection of research materials on SSL for non-sequential tabular data (SSL4NSTD)
[AAAI 2023] The implementation for the paper "Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs"
Self-supervised models for encoding protein localization patterns from microscopy images
[Survey] Awesome List of Mixup Augmentation and Beyond (https://arxiv.org/abs/2409.05202)
Curated List of papers on Self-Supervised Representation Learning
DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
A python library for self-supervised learning on images.
Self-supervised deep learning for denoising and missing wedge reconstruction of cryo-ET tomograms
LiBai(李白): A Toolbox for Large-Scale Distributed Parallel Training
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. arXiv:2307.09218.
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