📏 AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video Recognition

Github: https://github.com/leaplabthu/adafocusv2

Paper: https://arxiv.org/abs/2112.14238v1

Tasks: https://paperswithcode.com/task/video-recognition

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✨ Papers with Code 2021 : A Year in Review

https://www.kdnuggets.com/2021/12/2021-year-review-amazing-ai-papers.html

https://medium.com/paperswithcode/papers-with-code-2021-a-year-in-review-de75d5a77b8b

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🔼 PyramidTNT: Improved Transformer-in-Transformer Baselines with Pyramid Architecture

PyramidTNT achieves better performances than the previous state-of-the-art vision transformers such as Swin Transformer

Github: https://github.com/huawei-noah/CV-backbones

Paper: https://arxiv.org/abs/2201.00978v1

GhostNet: https://github.com/huawei-noah/CV-backbones/tree/master/ghostnet_pytorch

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🗣 AV-HuBERT (Audio-Visual Hidden Unit BERT)

AV-HuBERT is a self-supervised representation learning framework for audio-visual speech.

Github: https://github.com/facebookresearch/av_hubert

Facebook AI: https://ai.facebook.com/blog/ai-that-understands-speech-by-looking-as-well-as-hearing/

Paper: https://arxiv.org/abs/2201.02184

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🐭 pymdp: A Python library for active inference in discrete state spaces

Github: https://github.com/infer-actively/pymdp

Paper: https://arxiv.org/abs/2201.03904v1

Docs: https://pymdp-rtd.readthedocs.io/

Tasks: https://paperswithcode.com/task/bayesian-inference

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✨ Uniformer: Unified Transformer for Efficient Spatiotemporal Representation Learning

Github: https://github.com/sense-x/uniformer

Paper: https://arxiv.org/abs/2201.04676v1

Tasks: https://paperswithcode.com/dataset/kinetics-600

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💡 Introducing StylEx: A New Approach for Visual Explanation of Classifiers

Github: https://explaining-in-style.github.io/

Code: https://github.com/google/explaining-in-style

Article: https://ai.googleblog.com/2022/01/introducing-stylex-new-approach-for.html

Video: https://explaining-in-style.github.io/#video

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🔝 Omnivore: A Single Model for Many Visual Modalities

Github: https://github.com/facebookresearch/omnivore

Code: https://github.com/facebookresearch/omnivore/blob/main/inference_tutorial.ipynb

Paper: https://arxiv.org/abs/2201.08377

Dataset: https://paperswithcode.com/dataset/epic-kitchens-100

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🔥 The first high-performance self-supervised algorithm that works for speech, vision, and text

Github: https://github.com/pytorch/fairseq/tree/main/examples/data2vec

Paper: https://ai.facebook.com/research/data2vec-a-general-framework-for-self-supervised-learning-in-speech-vision-and-language

Meta AI: https://ai.facebook.com/blog/the-first-high-performance-self-supervised-algorithm-that-works-for-speech-vision-and-text/

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ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer

Github: https://github.com/locuslab/convmixer

Paper: https://arxiv.org/pdf/2201.09792v1.pdf

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⚪ Pearl: Parallel Evolutionary and Reinforcement Learning Library

Github: https://github.com/locuslab/convmixer

Paper: https://arxiv.org/pdf/2201.09568v1.pdf

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📎 When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism

Github: https://github.com/microsoft/SPACH

Paper: https://arxiv.org/abs/2201.10801v1

Dataset: https://paperswithcode.com/dataset/coco

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🔉 PortaSpeech: Portable and High-Quality Generative Text-to-Speech

Github: https://github.com/keonlee9420/PortaSpeech

Paper: https://arxiv.org/pdf/2109.15166v4.pdf

Dataset: https://paperswithcode.com/dataset/ljspeech

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Исследователи в области компьютерных наук могут получить миллион рублей от Яндекса!

До 20 марта открыт прием заявок на научную премию имени Ильи Сегаловича. Подать заявку могут студенты, аспиранты и научные руководители, которые занимаются распознаванием и синтезом речи, информационным поиском, машинным обучением, компьютерным зрением, обработкой естественного языка и машинным переводом.

Лауреаты премии получат:

— один миллион рублей
— оплачиваемую поездку на международную конференцию по AI
— гранты на использование сервисов Яндекс.Толока и Yandex DataSphere для своих исследований

Подробности по ссылке: https://clck.ru/amsXS

📹 VRT: A Video Restoration Transformer

Github: https://github.com/jingyunliang/vrt

Paper: https://arxiv.org/abs/2201.12288

Dataset: https://paperswithcode.com/dataset/gopro

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📍 Competition-Level Code Generation with AlphaCode

Github: https://github.com/deepmind/code_contests

Paper: https://storage.googleapis.com/deepmind-media/AlphaCode/competition_level_code_generation_with_alphacode.pdf

Dataset: https://paperswithcode.com/dataset/humaneval

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VOS: Learning What You Don't Know by Virtual Outlier Synthesis

Github: https://github.com/deeplearning-wisc/vos

Paper: https://arxiv.org/pdf/2202.01197v2.pdf

Dataset: https://paperswithcode.com/dataset/bdd100k

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🦾 The easiest way to the neuroscience world with the shield for RaspberryPi

Github: https://github.com/Ildaron/EEGwithRaspberryPI

Paper: https://arxiv.org/pdf/2202.01936v1.pdf

Project: https://www.crowdsupply.com/hackerbci/pieeg

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🖌 Two-Dimensional Tensors in Pytorch

https://machinelearningmastery.com/two-dimensional-tensors-in-pytorch/

One-Dimensional Tensors: https://machinelearningmastery.com/one-dimensional-tensors-in-pytorch/

PyTorch tensor Tutorial: https://pytorch.org/tutorials/beginner/basics/tensorqs_tutorial.html

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🗒 DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers

Github: https://github.com/j-min/dalleval

Paper: https://arxiv.org/pdf/2202.01936v1.pdf

Data: https://drive.google.com/drive/folders/1Bza2zyvHLvComohZ9PAGyykY7sm7JoIH

Dataset: https://paperswithcode.com/dataset/conceptual-captions

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https://news.1rj.ru/str/Machinelearningtest - machine learning tests