Generating Cats with StyleGAN on AWS SageMaker
https://devopstar.com/2019/02/25/generating-cats-with-stylegan-on-aws-sagemaker
Code: https://github.com/t04glovern/stylegan
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https://devopstar.com/2019/02/25/generating-cats-with-stylegan-on-aws-sagemaker
Code: https://github.com/t04glovern/stylegan
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AI predicts effective drug combinations to fight complex diseases faster
https://ai.facebook.com/blog/ai-predicts-effective-drug-combinations-to-fight-complex-diseases-faster/
Github: https://github.com/facebookresearch/CPA
Paper: https://www.biorxiv.org/content/10.1101/2021.04.14.439903v1
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https://ai.facebook.com/blog/ai-predicts-effective-drug-combinations-to-fight-complex-diseases-faster/
Github: https://github.com/facebookresearch/CPA
Paper: https://www.biorxiv.org/content/10.1101/2021.04.14.439903v1
@ArtificialIntelligencedl
Essential Math for Data Science: Linear Transformation with Matrices
https://hadrienj.github.io/posts/Essential-Math-for-Data-Science-linear_transformations/
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https://hadrienj.github.io/posts/Essential-Math-for-Data-Science-linear_transformations/
@ArtificialIntelligencedl
🐙 OCTIS : Optimizing and Comparing Topic Models is Simple!
Github: https://github.com/mind-Lab/octis
Paper: https://www.aclweb.org/anthology/2021.eacl-demos.31/
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Github: https://github.com/mind-Lab/octis
Paper: https://www.aclweb.org/anthology/2021.eacl-demos.31/
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GitHub
GitHub - MIND-Lab/OCTIS: OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted…
OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track) - MIND-Lab/OCTIS
DomainBed is a PyTorch suite containing benchmark datasets and algorithms for domain generalization
Github: https://github.com/facebookresearch/DomainBed
Paper: https://arxiv.org/abs/2104.09937v1
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Github: https://github.com/facebookresearch/DomainBed
Paper: https://arxiv.org/abs/2104.09937v1
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GitHub
GitHub - facebookresearch/DomainBed: DomainBed is a suite to test domain generalization algorithms
DomainBed is a suite to test domain generalization algorithms - facebookresearch/DomainBed
Forwarded from TensorFlow
Evolving Reinforcement Learning Algorithms
https://ai.googleblog.com/2021/04/evolving-reinforcement-learning.html
@tensorflowblog
https://ai.googleblog.com/2021/04/evolving-reinforcement-learning.html
@tensorflowblog
research.google
Evolving Reinforcement Learning Algorithms
Posted by John D. Co-Reyes, Research Intern and Yingjie Miao, Senior Software Engineer, Google Research A long-term, overarching goal of research i...
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
Github: https://github.com/W-zx-Y/DANNet
Paper: https://arxiv.org/abs/2104.10834
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Github: https://github.com/W-zx-Y/DANNet
Paper: https://arxiv.org/abs/2104.10834
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NISQA: Speech Quality and Naturalness Assessment
Github: https://github.com/gabrielmittag/NISQA
Paper: https://arxiv.org/abs/2104.11673v1
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Github: https://github.com/gabrielmittag/NISQA
Paper: https://arxiv.org/abs/2104.11673v1
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GitHub
GitHub - gabrielmittag/NISQA: NISQA - Non-Intrusive Speech Quality and TTS Naturalness Assessment
NISQA - Non-Intrusive Speech Quality and TTS Naturalness Assessment - gabrielmittag/NISQA
MDETR: Modulated Detection for End-to-End Multi-Modal Understanding
Github: https://github.com/ashkamath/mdetr
Paper: https://arxiv.org/abs/2104.12763
Colab: https://colab.research.google.com/github/ashkamath/mdetr/blob/colab/notebooks/MDETR_demo.ipynb
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Github: https://github.com/ashkamath/mdetr
Paper: https://arxiv.org/abs/2104.12763
Colab: https://colab.research.google.com/github/ashkamath/mdetr/blob/colab/notebooks/MDETR_demo.ipynb
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MMEditing is an open source image and video editing toolbox based on PyTorch.
Github: https://github.com/open-mmlab/mmediting
Docs: https://mmediting.readthedocs.io/en/latest/
Paper: https://arxiv.org/abs/2104.13371v1
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Github: https://github.com/open-mmlab/mmediting
Docs: https://mmediting.readthedocs.io/en/latest/
Paper: https://arxiv.org/abs/2104.13371v1
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PyTorch Tabular aims to make Deep Learning with Tabular data easy and accessible to real-world cases and research alike.
Github: https://github.com/manujosephv/pytorch_tabular
Paper: https://arxiv.org/abs/2104.13638v1
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Github: https://github.com/manujosephv/pytorch_tabular
Paper: https://arxiv.org/abs/2104.13638v1
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Boosting Co-teaching with Compression Regularization for Label Noise
Github: https://github.com/yingyichen-cyy/Nested-Co-teaching
Paper: https://arxiv.org/abs/2104.13766v1
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Github: https://github.com/yingyichen-cyy/Nested-Co-teaching
Paper: https://arxiv.org/abs/2104.13766v1
@ArtificialIntelligencedl
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LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search
Github: https://github.com/researchmm/LightTrack
Paper: https://arxiv.org/abs/2104.14545v1
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Github: https://github.com/researchmm/LightTrack
Paper: https://arxiv.org/abs/2104.14545v1
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Few-Shot Video Object Detection
Github: https://github.com/fanq15/FewX
Paper: https://arxiv.org/abs/2104.14805v1
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Github: https://github.com/fanq15/FewX
Paper: https://arxiv.org/abs/2104.14805v1
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StyleMapGAN - Official PyTorch Implementation
Github: https://github.com/naver-ai/StyleMapGAN
Paper: https://arxiv.org/abs/2104.14754v1
Video: https://youtu.be/qCapNyRA_Ng
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Github: https://github.com/naver-ai/StyleMapGAN
Paper: https://arxiv.org/abs/2104.14754v1
Video: https://youtu.be/qCapNyRA_Ng
@ArtificialIntelligencedl
Python implementation of the Bayesian Knowledge Tracing algorithm and variants, estimating student cognitive mastery from problem solving sequences.
Github: https://github.com/CAHLR/pyBKT
Tutorial: https://colab.research.google.com/drive/13abu919edUXbvPV3qeGPpvwnFBExU7Vd
Paper: https://arxiv.org/abs/2105.00385v1
Github: https://github.com/CAHLR/pyBKT
Tutorial: https://colab.research.google.com/drive/13abu919edUXbvPV3qeGPpvwnFBExU7Vd
Paper: https://arxiv.org/abs/2105.00385v1
GitHub
GitHub - CAHLR/pyBKT: Python implementation of Bayesian Knowledge Tracing and extensions
Python implementation of Bayesian Knowledge Tracing and extensions - CAHLR/pyBKT
Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet
Github: https://github.com/lukemelas/do-you-even-need-attention
Paper: https://arxiv.org/abs/2105.02723
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Github: https://github.com/lukemelas/do-you-even-need-attention
Paper: https://arxiv.org/abs/2105.02723
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Deep Implicit Attention: A Mean-Field Theory Perspective on Attention Mechanisms
https://mcbal.github.io/post/deep-implicit-attention-a-mean-field-theory-perspective-on-attention-mechanisms/
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https://mcbal.github.io/post/deep-implicit-attention-a-mean-field-theory-perspective-on-attention-mechanisms/
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mcbal
Deep Implicit Attention: A Mean-Field Theory Perspective on Attention Mechanisms | mcbal
Can we model attention as the collective response of a statistical-mechanical system?
Two4Two: Evaluating Interpretable Machine Learning -- A Synthetic Dataset For Controlled Experiments
Github: https://github.com/mschuessler/two4two
Paper: https://arxiv.org/abs/2105.02825v1
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Github: https://github.com/mschuessler/two4two
Paper: https://arxiv.org/abs/2105.02825v1
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Body Meshes as Points
Github: https://github.com/jfzhang95/BMP
Paper: https://arxiv.org/abs/2105.02467v1
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Github: https://github.com/jfzhang95/BMP
Paper: https://arxiv.org/abs/2105.02467v1
@ArtificialIntelligencedl
Chimera: Learning Shared Semantic Space for Speech-to-Text Translation (Nightly Version)
Github: https://github.com/Glaciohound/Chimera-SLT
Paper: https://arxiv.org/abs/2105.03095
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Github: https://github.com/Glaciohound/Chimera-SLT
Paper: https://arxiv.org/abs/2105.03095
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