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The Illustrated FixMatch for Semi-Supervised Learning
Learn how to leverage unlabeled data using FixMatch for semi-supervised learning
semi-supervised-learning computer-vision pytorch illustrated-series
Self-Supervised Scene De-occlusion
We investigate the problem of scene de-occlusion, which aims to recover the underlying occlusion ordering and complete the invisible parts of occluded ...
self-supervised-learning computer-vision de-occlusion research
Finetuning Transformers with JAX + Haiku
Walking through a port of the RoBERTa pre-trained model to JAX + Haiku, then fine-tuning the model to solve a downstream task.
jax haiku roberta transformers
torchlayers
Library based on PyTorch providing automatic shape and dimensionality inference of torch.nn layers + additional building blocks.
pytorch library toolkit
Talking-Heads Attention
A variation on multi-head attention which includes linear projections across the attention-heads dimension, immediately before and after the softmax ...
multi-head-attention talking-heads-attention attention transformers
Meta Pseudo Labels
We all know about meta-learning and pseudo labeling but what if we combine the two techniques for semi-supervised learning? Can it be any beneficial?
semi-supervised-learning meta-learning machine-learning deep-learning
Towards an ImageNet Moment for Speech-to-Text
An overview of the conditions met by the Speech-to-Text ML subfield to reach the ImageNet moment.
speech-recognition speech-to-text asr russian
How to setup a local AWS SageMaker environment for PyTorch
Learn how to develop an ML app for a PyTorch Model faster by using AWS SageMaker local mode vs. deploying directly to AWS.
pytorch sagemaker web-services web-app
TransMoMo: Invariance-Driven Unsupervised Motion Retargeting
A lightweight video motion retargeting approach that is capable of transferring motion of a person in a source video realistically to another video of a ...
motion-generation video retargeting transmomo
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