Hello everyone. My name is Andrew and for several years I've been working on to make the learning path for ML
easier.

I wrote a manual on machine learning that
everyone understands - Machine Learning Simplified Book. The main purpose of my book is to build an intuitive
understanding of how algorithms work through basic examples. In order to understand the presented material,
it is enough to know basic mathematics and linear algebra.

After reading this book, you will know the basics of supervised learning, understand complex mathematical models, understand the entire pipeline of a typical ML project, and also be able to share your knowledge with colleagues from related industries and with technical
professionals.


You can read the book absolutely free at the link below:
-> https://themlsbook.com

⚫️ Beyond 3D Siamese Tracking: A Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds

Github: https://github.com/ghostish/open3dsot

Paper: https://arxiv.org/abs/2203.01730v1

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

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🎓 StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generation

Github: https://github.com/royorel/StyleSDF

Paper: https://arxiv.org/abs/2112.11427v1

Project: https://stylesdf.github.io/

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

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🔲 Kubric A data generation pipeline for creating semi-realistic synthetic multi-object videos

Github: https://github.com/google-research/kubric

Paper: https://arxiv.org/abs/2203.03570v1

Docs: https://kubric.readthedocs.io/

Dataset: https://github.com/deepmind/multi_object_datasets

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♟ Probabilistic Warp Consistency for Weakly-Supervised Semantic Correspondences

Github: https://github.com/PruneTruong/DenseMatching

Paper: https://arxiv.org/abs/2203.04279v1

Project: https://prunetruong.com/research/warpc

Dataset: https://paperswithcode.com/dataset/pf-pascal

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🗿 StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis

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

Video: http://jiataogu.me/style_nerf

Paper: https://arxiv.org/abs/2110.08985

Project: http://jiataogu.me/style_nerf/

Dataset: https://github.com/facebookresearch/StyleNeRF#dataset

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https://news.1rj.ru/str/datascienceml_jobs - data science and ml jobs

💥 A Single Correspondence Is Enough: Robust Global Registration to Avoid Degeneracy in Urban Environments

Github: https://github.com/url-kaist/quatro

Video: http://jiataogu.me/style_nerf

Paper: https://arxiv.org/abs/2203.06612v1

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

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🦾 Test Suites for Validating ML Models & Data

Github: https://github.com/deepchecks/deepchecks

Example: https://docs.deepchecks.com/en/stable/examples/guides/quickstart_in_5_minutes.html

Docs: https://docs.deepchecks.com/

Paper: https://arxiv.org/abs/2203.08491v1

Blog: https://deepchecks.com/blog/

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🧷 HybridNets: End2End Perception Network

Github: https://github.com/datvuthanh/HybridNets

Paper: https://arxiv.org/abs/2203.09035v1

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

Tasks: https://paperswithcode.com/task/traffic-object-detection

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💬 A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolution

Github: https://github.com/mjq11302010044/tatt

Paper: https://arxiv.org/abs/2203.09388v2

Dataset: https://deepchecks.com/blog/

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〰 Monotonic Differentiable Sorting Networks

Github: https://github.com/Felix-Petersen/diffsort

Colab: https://colab.research.google.com/drive/1q0TZFFYB9FlOJYWKt0_7ZaXQT190anhm?usp=sharing

Paper: https://arxiv.org/abs/2203.09630v1

Video: https://www.youtube.com/watch?v=Rl-sFaE1z4M

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

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⚡️ EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

Article

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💭 NeuralSpeech is a research project in focusing on neural network based speech processing

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

Paper: https://arxiv.org/pdf/2109.14420v3.pdf

Speech Research: https://speechresearch.github.io/

Dataset: https://paperswithcode.com/dataset/aishell-1

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🔎 BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training

Github: https://github.com/amazon-research/bigdetection

Paper: https://arxiv.org/abs/2203.13249v1

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

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🎨 Autoregressive Image Generation using Residual Quantization

Github: https://github.com/kakaobrain/rq-vae-transformer

Pytorch: https://github.com/lucidrains/vector-quantize-pytorch

Paper: https://arxiv.org/abs/2203.01941v2

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

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🎨 Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer

Github: https://github.com/williamyang1991/DualStyleGAN

Paper: https://arxiv.org/abs/2203.13248v1

Video: https://www.youtube.com/watch?v=scZTu77jixI

Project: https://www.mmlab-ntu.com/project/dualstylegan/

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

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🤖 REGTR: End-to-end Point Cloud Correspondences with Transformers

Github: https://github.com/yewzijian/regtr

Paper: https://arxiv.org/abs/2203.14517v1

Pretrained models: https://github.com/yewzijian/RegTR/releases/download/v1/trained_models.zip

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

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⛓ Deep Automatic Natural Image Matting

Github: https://github.com/JizhiziLi/AIM

Paper: https://arxiv.org/abs/2107.07235

Pretrained models: https://drive.google.com/uc?export=download&id=16dd1FGMcsMTqR6EfD2T9mtRmPwxnY0zs

Dataset: https://paperswithcode.com/dataset/celebamask-hq

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SuperGAT

A self-supervised graph attention network (SuperGAT), an improved graph attention model for noisy graph

Code: https://github.com/dongkwan-kim/SuperGAT

Paper: https://arxiv.org/abs/2204.04879v1

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

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