LightSeq: A High Performance Library for Sequence Processing and Generation

Github: https://github.com/bytedance/lightseq

Paper: https://arxiv.org/abs/2110.05722v1

A Guide of LightSeq Training: https://github.com/bytedance/lightseq/blob/master/docs/guide.md

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📊ByteTrack: Multi-Object Tracking by Associating Every Detection Box

Github: https://github.com/ifzhang/ByteTrack

Paper: https://arxiv.org/abs/2110.06864

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

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🍾 Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)

Github: https://github.com/jbeomlee93/rib

Paper: http://arxiv.org/abs/2110.06530

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

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📖 Bayesian Optimization Book 2021

Book: https://bayesoptbook.com

Github: https://github.com/bayesoptbook/bayesoptbook.github.io

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ESPnet2-TTS: Extending the Edge of TTS Research

Github: https://github.com/espnet/espnet

Docs: https://espnet.github.io/espnet/

Paper: https://arxiv.org/abs/2110.07840v1

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

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🧵 abess: Fast Best-Subset Selection in Python and R

Github: https://github.com/abess-team/abess

Docs: https://abess.readthedocs.io/en/latest/Tutorial/index.html

Paper: https://arxiv.org/abs/2110.09697v1


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📄 HRFormer: High-Resolution Transformer for Dense Prediction, NeurIPS 2021

Github: https://github.com/HRNet/HRFormer

Paper: https://arxiv.org/abs/2110.09408v1

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

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⚙️SecureBoost+ : A High Performance Gradient Boosting Tree Framework for Large Scale Vertical Federated Learning

Github: https://github.com/FederatedAI/FATE

Paper: https://arxiv.org/abs/2110.10927v1

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🅱️ Bi-directional Image and Text Generation

Github: https://github.com/researchmm/generate-it

Paper: https://arxiv.org/abs/2110.09753v1

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

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📌 PyTorch: Transfer Learning and Image Classification

https://www.pyimagesearch.com/2021/10/11/pytorch-transfer-learning-and-image-classification/

Dataset: https://www.tensorflow.org/datasets/catalog/tf_flowers

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🚀 NAS-FCOS: Fast Neural Architecture Search for Object Detection

Github: https://github.com/Lausannen/NAS-FCOS

Paper: https://arxiv.org/abs/2110.12423v1


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🌲 Revisiting randomized choices in isolation forests

Github: https://github.com/david-cortes/isotree

Paper: https://arxiv.org/abs/2110.13402v1

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😃 GoEmotions: A Dataset for Fine-Grained Emotion Classification

Github: https://github.com/google-research/google-research/tree/master/goemotions

Google AI: https://ai.googleblog.com/2021/10/goemotions-dataset-for-fine-grained.html

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🪛 OneFlow is a performance-centered and open-source deep learning framework.

Github: https://github.com/Oneflow-Inc/oneflow

Paper: https://arxiv.org/abs/2110.15032v2

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🖼 StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

Github: https://github.com/POSTECH-CVLab/PyTorch-StudioGAN

Paper: https://arxiv.org/abs/2111.01118v1

Dataset: https://paperswithcode.com/dataset/cifar-10

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Что прямо сейчас происходит в российских компьютерных науках?

Канал «Русские норм!» поговорил с учеными из Яндекса и узнал, насколько хорошо нейросети рисуют логотипы и пишут шансон и какие нюансы нужно учесть, чтобы запустить беспилотники на улицы.

Чему сейчас учат искусственный интеллект?
Что такое графы и как их используют в современных приложениях?
Что мешает роботам ориентироваться в реальном мире и можем ли мы им помочь?

Актуальное о Machine Learning и нейросетях — смотрите в выпуске «Ученые норм!».

🎯 Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees

Github: https://github.com/AaltoML/BayesNewton

Paper: https://arxiv.org/abs/2111.01721v1

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📏 OpenPrompt: An Open-source Framework for Prompt-learning

Github: https://github.com/thunlp/OpenPrompt

Paper: https://arxiv.org/abs/2111.01998v1


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⚡️ Alias-Free Generative Adversarial Networks (StyleGAN3)

Github: https://github.com/pdillis/stylegan3-fun

Paper: https://arxiv.org/abs/2111.02175v1

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

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👁‍🗨 OCR Post Correction for Endangered Language Texts

Github: https://github.com/shrutirij/ocr-post-correction

Paper: https://arxiv.org/abs/2111.02622v1

Docs: https://shrutirij.github.io/ocr-el/

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🔵 BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning

Github: https://github.com/Bluefog-Lib/bluefog

Paper: https://arxiv.org/abs/2111.04287v1

Docs: https://bluefog-lib.github.io/bluefog/performance.html

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