🔥 Model Search by Google
Automatically build and deploy state-of-the-art machine learning models on structured data.
Github: https://github.com/google/model_search
Paper: https://pdfs.semanticscholar.org/1bca/d4cdfbc01fbb60a815660d034e561843d67a.pdf
Project: https://cloud.google.com/automl-tables
@ai_machinelearning_big_data
Automatically build and deploy state-of-the-art machine learning models on structured data.
Github: https://github.com/google/model_search
Paper: https://pdfs.semanticscholar.org/1bca/d4cdfbc01fbb60a815660d034e561843d67a.pdf
Project: https://cloud.google.com/automl-tables
@ai_machinelearning_big_data
🚀 DALL-E Zero-Shot Text-to-Image Generation
Github: https://github.com/openai/DALL-E
Paper: https://arxiv.org/abs/2102.12092
OpenAi: https://openai.com/blog/dall-e/
@ai_machinelearning_big_data
Github: https://github.com/openai/DALL-E
Paper: https://arxiv.org/abs/2102.12092
OpenAi: https://openai.com/blog/dall-e/
@ai_machinelearning_big_data
GitHub
GitHub - openai/DALL-E: PyTorch package for the discrete VAE used for DALL·E.
PyTorch package for the discrete VAE used for DALL·E. - openai/DALL-E
When Attention Meets Fast Recurrence: Training Language Models with Reduced Compute
Github: https://github.com/asappresearch/sru
Paper: https://arxiv.org/abs/2102.12459v1
Project: https://www.asapp.com/blog/reducing-the-high-cost-of-training-nlp-models-with-sru/
@ai_machinelearning_big_data
Github: https://github.com/asappresearch/sru
Paper: https://arxiv.org/abs/2102.12459v1
Project: https://www.asapp.com/blog/reducing-the-high-cost-of-training-nlp-models-with-sru/
@ai_machinelearning_big_data
GitHub
GitHub - asappresearch/sru: Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)
Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755) - asappresearch/sru
XLA: Optimizing Compiler for Machine Learning
Tensorflow: https://www.tensorflow.org/xla
XLA Architecture: https://www.tensorflow.org/xla/architecture
Github: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/compiler/xla
Code: https://www.tensorflow.org/xla/tutorials/jit_compile
@ai_machinelearning_big_data
Tensorflow: https://www.tensorflow.org/xla
XLA Architecture: https://www.tensorflow.org/xla/architecture
Github: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/compiler/xla
Code: https://www.tensorflow.org/xla/tutorials/jit_compile
@ai_machinelearning_big_data
⭐ CelebA-Spoof: Large-Scale Face Anti-Spoofing Dataset with Rich Annotations
Github: https://github.com/Davidzhangyuanhan/CelebA-Spoof
Paper: https://arxiv.org/abs/2102.12642v2
Dataset: https://drive.google.com/drive/folders/1OW_1bawO79pRqdVEVmBzp8HSxdSwln_Z
Video: https://www.youtube.com/watch?v=A7XjSg5srvI&t=4s&ab_channel=YuanhanZhang
@ai_machinelearning_big_data
Github: https://github.com/Davidzhangyuanhan/CelebA-Spoof
Paper: https://arxiv.org/abs/2102.12642v2
Dataset: https://drive.google.com/drive/folders/1OW_1bawO79pRqdVEVmBzp8HSxdSwln_Z
Video: https://www.youtube.com/watch?v=A7XjSg5srvI&t=4s&ab_channel=YuanhanZhang
@ai_machinelearning_big_data
🔥1
CogDL: An Extensive Research Toolkit for Deep Learning on Graphs
http://keg.cs.tsinghua.edu.cn/cogdl/
Github: https://github.com/THUDM/cogdl
Paper: https://arxiv.org/abs/2103.00959
Dateset: https://github.com/THUDM/cogdl/blob/master/cogdl/datasets/README.md
@ai_machinelearning_big_data
http://keg.cs.tsinghua.edu.cn/cogdl/
Github: https://github.com/THUDM/cogdl
Paper: https://arxiv.org/abs/2103.00959
Dateset: https://github.com/THUDM/cogdl/blob/master/cogdl/datasets/README.md
@ai_machinelearning_big_data
🤖 A Text-to-Speech Transformer in TensorFlow 2
Github: https://github.com/as-ideas/TransformerTTS
Paper: https://arxiv.org/abs/2103.00993v1
Samples: https://as-ideas.github.io/TransformerTTS/
@ai_machinelearning_big_data
Github: https://github.com/as-ideas/TransformerTTS
Paper: https://arxiv.org/abs/2103.00993v1
Samples: https://as-ideas.github.io/TransformerTTS/
@ai_machinelearning_big_data
🧠 Multimodal Neurons in Artificial Neural Networks
https://openai.com/blog/multimodal-neurons/
Github: https://github.com/openai/CLIP-featurevis
Paper: https://distill.pub/2021/multimodal-neurons/
@ai_machinelearning_big_data
https://openai.com/blog/multimodal-neurons/
Github: https://github.com/openai/CLIP-featurevis
Paper: https://distill.pub/2021/multimodal-neurons/
@ai_machinelearning_big_data
Openai
Multimodal neurons in artificial neural networks
We’ve discovered neurons in CLIP that respond to the same concept whether presented literally, symbolically, or conceptually. This may explain CLIP’s accuracy in classifying surprising visual renditions of concepts, and is also an important step toward understanding…
Register for the International Data Analysis Olympiad (IDAO-2021)! The registration continues until March 12.
This year, HSE Faculty of Computer Science and Yandex are holding the Olympiad for the fourth time. This year's Platinum Partner is ‘Otkritie’ Bank. The Olympiad is organised by leading data analysts for their future colleagues, early career analysts and scientists.
The online tour will focus on the search for dark matter - one of the few remaining mysteries of fundamental physics. Dark matter cannot be seen because it does not interact with light and interacts very weakly with ordinary matter. The task of IDAO participants is to build a model that recognises some known observation processes, so that they can be excluded from the search for dark matter.
Details and registration https://idao.world
This year, HSE Faculty of Computer Science and Yandex are holding the Olympiad for the fourth time. This year's Platinum Partner is ‘Otkritie’ Bank. The Olympiad is organised by leading data analysts for their future colleagues, early career analysts and scientists.
The online tour will focus on the search for dark matter - one of the few remaining mysteries of fundamental physics. Dark matter cannot be seen because it does not interact with light and interacts very weakly with ordinary matter. The task of IDAO participants is to build a model that recognises some known observation processes, so that they can be excluded from the search for dark matter.
Details and registration https://idao.world
This media is not supported in your browser
VIEW IN TELEGRAM
Anycost GAN
Anycost GANs for Interactive Image Synthesis and Editing
https://hanlab.mit.edu/projects/anycost-gan/
Github: https://github.com/mit-han-lab/anycost-gan
Paper: https://arxiv.org/abs/2103.03243
@ai_machinelearning_big_data
Anycost GANs for Interactive Image Synthesis and Editing
https://hanlab.mit.edu/projects/anycost-gan/
Github: https://github.com/mit-han-lab/anycost-gan
Paper: https://arxiv.org/abs/2103.03243
@ai_machinelearning_big_data
RTAB-Map
Real-Time Appearance-Based Mapping
http://introlab.github.io/rtabmap/
Github: https://github.com/introlab/rtabmap
Paper: https://arxiv.org/abs/2103.03827v1
@ai_machinelearning_big_data
Real-Time Appearance-Based Mapping
http://introlab.github.io/rtabmap/
Github: https://github.com/introlab/rtabmap
Paper: https://arxiv.org/abs/2103.03827v1
@ai_machinelearning_big_data
GitHub
GitHub - introlab/rtabmap: RTAB-Map library and standalone application
RTAB-Map library and standalone application. Contribute to introlab/rtabmap development by creating an account on GitHub.
Precise Multi-Neuron Abstractions for Neural Network Certification
Github : https://github.com/eth-sri/eran
Paper: https://arxiv.org/abs/2103.03638v1
@ai_machinelearning_big_data
Github : https://github.com/eth-sri/eran
Paper: https://arxiv.org/abs/2103.03638v1
@ai_machinelearning_big_data
👔 Virtual Try-on via Distilling Appearance Flows, CVPR 2021
Github: https://github.com/geyuying/PF-AFN
Paper: https://arxiv.org/abs/2103.04559
@ai_machinelearning_big_data
Github: https://github.com/geyuying/PF-AFN
Paper: https://arxiv.org/abs/2103.04559
@ai_machinelearning_big_data
Train and serve a TensorFlow model with TensorFlow Serving
https://www.tensorflow.org/tfx/tutorials/serving/rest_simple
Code: https://github.com/tensorflow/tfx/blob/master/docs/tutorials/serving/rest_simple.ipynb
Dataset: https://github.com/zalandoresearch/fashion-mnist
@ai_machinelearning_big_data
https://www.tensorflow.org/tfx/tutorials/serving/rest_simple
Code: https://github.com/tensorflow/tfx/blob/master/docs/tutorials/serving/rest_simple.ipynb
Dataset: https://github.com/zalandoresearch/fashion-mnist
@ai_machinelearning_big_data
TensorFlow
Train and serve a TensorFlow model with TensorFlow Serving | TFX
Involution: Inverting the Inherence of Convolution for Visual Recognition
Github: https://github.com/d-li14/involution
Paper: https://arxiv.org/abs/2103.06255
OpenMMLab: https://openmmlab.com/
@ai_machinelearning_big_data
Github: https://github.com/d-li14/involution
Paper: https://arxiv.org/abs/2103.06255
OpenMMLab: https://openmmlab.com/
@ai_machinelearning_big_data
This media is not supported in your browser
VIEW IN TELEGRAM
Strawberry Fields is a full-stack Python library for designing, simulating, and optimizing continuous-variable quantum optical circuits.
Github: https://github.com/XanaduAI/strawberryfields
Paper: https://arxiv.org/pdf/2103.05530v1.pdf
@ai_machinelearning_big_data
Github: https://github.com/XanaduAI/strawberryfields
Paper: https://arxiv.org/pdf/2103.05530v1.pdf
@ai_machinelearning_big_data
MagFace: A Universal Representation for Face Recognition and Quality Assessment
Github: https://github.com/IrvingMeng/MagFace
Paper: https://arxiv.org/abs/2103.06627
Code example: https://github.com/IrvingMeng/MagFace/blob/main/inference/examples.ipynb
@ai_machinelearning_big_data
Github: https://github.com/IrvingMeng/MagFace
Paper: https://arxiv.org/abs/2103.06627
Code example: https://github.com/IrvingMeng/MagFace/blob/main/inference/examples.ipynb
@ai_machinelearning_big_data
Develop a Neural Network for Banknote Authentication
https://machinelearningmastery.com/neural-network-for-banknote-authentication/
@ai_machinelearning_big_data
https://machinelearningmastery.com/neural-network-for-banknote-authentication/
@ai_machinelearning_big_data
🔥1
This media is not supported in your browser
VIEW IN TELEGRAM
Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion
Github: https://github.com/hkchengrex/MiVOS
Paper: https://arxiv.org/pdf/2103.07941v1.pdf
@ai_machinelearning_big_data
Github: https://github.com/hkchengrex/MiVOS
Paper: https://arxiv.org/pdf/2103.07941v1.pdf
@ai_machinelearning_big_data
This media is not supported in your browser
VIEW IN TELEGRAM
Open Avatarify Photorealistic avatars for video-conferencing apps. Democratized.
Github: https://github.com/alievk/avatarify-python
Demo: https://www.youtube.com/watch?v=Q7LFDT-FRzs&feature=youtu.be&ab_channel=AliAliev
@ai_machinelearning_big_data
Github: https://github.com/alievk/avatarify-python
Demo: https://www.youtube.com/watch?v=Q7LFDT-FRzs&feature=youtu.be&ab_channel=AliAliev
@ai_machinelearning_big_data
Probabilistic two-stage detection
Two-stage object detectors that use class-agnostic one-stage detectors as the proposal network.
Github: https://github.com/xingyizhou/CenterNet2
Paper: https://arxiv.org/abs/2103.07461v1
@ai_machinelearning_big_data
Two-stage object detectors that use class-agnostic one-stage detectors as the proposal network.
Github: https://github.com/xingyizhou/CenterNet2
Paper: https://arxiv.org/abs/2103.07461v1
@ai_machinelearning_big_data