BigData
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Data Science : Big Data : Machine Learning : Deep Learning. По всем вопросам @evgenycarter
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Can CNNs Be More Robust Than Transformers?

CNN architectures without any attention-like operations that is as robust as, or even more robust than, Transformers.

Github: https://github.com/ucsc-vlaa/robustcnn

Paper: https://arxiv.org/abs/2206.03452v1

Dataset: https://paperswithcode.com/dataset/imagenet-r

👉 @bigdata_1
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LIVE- Towards Layer-wise Image Vectorization

New method to progressively generate a SVG that fits the raster image in a layer-wise fashion.

Github: https://github.com/picsart-ai-research/live-layerwise-image-vectorization

Project: https://ma-xu.github.io/LIVE/

Paper: https://arxiv.org/pdf/2206.04655v1.pdf

Colab: https://colab.research.google.com/drive/1s108WmqSVH9MILOjSAu29QyAEjExOWAP?usp=sharing

👉 @bigdata_1
DoWhy | An end-to-end library for causal inference

"DoWhy" is a Python library that aims to spark causal thinking and analysis.

Github: https://github.com/py-why/dowhy

Docs: https://py-why.github.io/dowhy/

Paper: https://arxiv.org/abs/2206.06821v1

Video: https://note.microsoft.com/MSR-Webinar-DoWhy-Library-Registration-On-Demand.html

👉 @bigdata_1
Object Structural Points Representation for Graph-based Semantic Monocular Localization and Mapping

PyGOD is a Python library for graph outlier detection (anomaly detection).

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

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

Paper: https://arxiv.org/abs/2206.10071v1

👉 @bigdata_1
StrengthNet

Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

Github: https://github.com/ttslr/strengthnet

Paper: https://arxiv.org/abs/2110.03156

MOSNet: https://github.com/lochenchou/MOSNet

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Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case

This library implements some of the most common (Variational) Autoencoder models.

Github: https://github.com/clementchadebec/benchmark_VAE

Paper: https://arxiv.org/abs/2206.08309v1

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

👉 @bigdata_1
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DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation

DaisyRec-v2.0 is a Python toolkit developed for benchmarking top-N recommendation task.

Github: https://github.com/recsys-benchmark/daisyrec-v2.0

Command Generator : http://daisyrecguicommandgenerator.pythonanywhere.com/

Paper: https://arxiv.org/abs/2206.10848v1

Tutorial: https://github.com/recsys-benchmark/DaisyRec-v2.0/blob/main/DaisyRec-v2.0-Tutorial.ipynb

👉 @bigdata_1
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SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning

We introduce SoundSpaces 2.0, a platform for on-the-fly geometry-based audio rendering for 3D environments.

Github: https://github.com/facebookresearch/sound-spaces

Paper: https://arxiv.org/abs/2206.08312v1

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

👉 @bigdata_1
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Frequency Dynamic Convolution-Recurrent Neural Network (FDY-CRNN) for Sound Event Detection

Frequency Dynamic Convolution applied kernel that adapts to each freqeuncy bin of input, in order to remove tranlation equivariance of 2D convolution along the frequency axis.

Github: https://github.com/frednam93/FDY-SED

Paper: https://arxiv.org/abs/2206.11645v1

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

👉 @bigdata_1
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Retrosynthetic Planning with Retro*

graph-based search policy that eliminates the redundant explorations of any intermediate molecules.

Github: https://github.com/binghong-ml/retro_star

Paper: https://arxiv.org/abs/2206.11477v1

Dataset: https://www.dropbox.com/s/ar9cupb18hv96gj/retro_data.zip?dl=0

👉 @bigdata_1
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Bi-DexHands: Bimanual Dexterous Manipulation via Reinforcement Learning

Bi-DexHands provides a collection of bimanual dexterous manipulations tasks and reinforcement learning algorithms.

Github: https://github.com/pku-marl/dexteroushands

Isaac Gym: https://developer.nvidia.com/isaac-gym

Paper: https://arxiv.org/abs/2206.08686

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MindWare: Efficient Open-source AutoML System

MindWare is an efficient open-source system to help users to automate the process of: 1) data pre-processing, 2) feature engineering, 3) algorithm selection, 4) architecture design, 5) hyper-parameter tuning, and 6) model ensembling.

Github: https://github.com/PKU-DAIR/mindware

Docs: https://mindware.readthedocs.io/en/latest/

Paper: https://arxiv.org/abs/2206.09423v1

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Tntorch - Tensor Network Learning with PyTorch

PyTorch-powered modeling and learning library using tensor networks. Installation: pip install tntorch

Github: https://github.com/rballester/tntorch

Docs site: http://tntorch.readthedocs.io/

Paper: https://arxiv.org/abs/2206.11128v1

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Prosody Cloning in Zero-Shot Multispeaker Text-to-Speech

IMS Toucan is a toolkit for teaching, training and using state-of-the-art Speech Synthesis models.

Github: https://github.com/rballester/tntorch

Pre-Generated Audios: https://multilingualtoucan.github.io/

Cloning prosody across speakers: https://toucanprosodycloningdemo.github.io/

Paper: https://arxiv.org/abs/2206.12229v1

👉 @bigdata_1
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Insubstantial Object Detection

Dataset comprised of 600 videos (141,017 frames) covering various distances, sizes, visibility, and scenes captured by different spectral ranges.

Github: https://github.com/calayzhou/iod-video

Project: https://calayzhou.github.io/

Paper: https://arxiv.org/abs/2206.11459v1

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

👉 @bigdata_1
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How to Grid Search Hyperparameters for Deep Learning Models in Python With Keras

https://machinelearningmastery.com/grid-search-hyperparameters-deep-learning-models-python-keras/

👉 @bigdata_1
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