Memory-Efficient Adaptive Optimization
Source: https://arxiv.org/abs/1901.11150
Code: https://github.com/google-research/google-research/tree/master/sm3
Source: https://arxiv.org/abs/1901.11150
Code: https://github.com/google-research/google-research/tree/master/sm3
arXiv.org
Memory-Efficient Adaptive Optimization
Adaptive gradient-based optimizers such as Adagrad and Adam are crucial for achieving state-of-the-art performance in machine translation and language modeling. However, these methods maintain...
Finally, AI-Based Painting is here!
#GANPaint
video: https://www.youtube.com/watch?v=IqHs_DkmDVo
Semantic Photo Manipulation with a Generative Image Prior
paper: https://ganpaint.io/
#GANPaint
video: https://www.youtube.com/watch?v=IqHs_DkmDVo
Semantic Photo Manipulation with a Generative Image Prior
paper: https://ganpaint.io/
YouTube
Finally, AI-Based Painting is Here!
❤️ Check out Weights & Biases here and sign up for a free demo: https://www.wandb.com/papers
📝 The paper "GANPaint Studio - Semantic Photo Manipulation with a Generative Image Prior" and its online demo are available here:
https://ganpaint.io/
🙏 We would…
📝 The paper "GANPaint Studio - Semantic Photo Manipulation with a Generative Image Prior" and its online demo are available here:
https://ganpaint.io/
🙏 We would…
Meta-Learning with Warped Gradient Descent
https://flennerhag.com/research/warped_gradient_descent.pdf
https://flennerhag.com/research/warped_gradient_descent.pdf
DeepFaceLab is a tool that utilizes machine learning to replace faces in videos
https://github.com/iperov/DeepFaceLab
https://github.com/iperov/DeepFaceLab
GitHub
GitHub - iperov/DeepFaceLab: DeepFaceLab is the leading software for creating deepfakes.
DeepFaceLab is the leading software for creating deepfakes. - iperov/DeepFaceLab
Generative Flow based Sequence-to-Sequence Toolkit written in Python.
https://github.com/XuezheMax/flowseq
https://github.com/XuezheMax/flowseq
GitHub
GitHub - XuezheMax/flowseq: Generative Flow based Sequence-to-Sequence Toolkit written in Python.
Generative Flow based Sequence-to-Sequence Toolkit written in Python. - XuezheMax/flowseq
From Machine Learning to Machine Reasoning
https://arxiv.org/abs/1102.1808
https://arxiv.org/abs/1102.1808
arXiv.org
From Machine Learning to Machine Reasoning
A plausible definition of "reasoning" could be "algebraically manipulating previously acquired knowledge in order to answer a new question". This definition covers first-order logical inference or...
Resources for Getting Started With Probability in Machine Learning
https://machinelearningmastery.com/probability-resources-for-machine-learning/
https://machinelearningmastery.com/probability-resources-for-machine-learning/
MachineLearningMastery.com
Resources for Getting Started With Probability in Machine Learning - MachineLearningMastery.com
Machine Learning is a field of computer science concerned with developing systems that can learn from data.
Like statistics and linear algebra, probability is another foundational field that supports machine learning. Probability is a field of mathematics…
Like statistics and linear algebra, probability is another foundational field that supports machine learning. Probability is a field of mathematics…
📝 The paper: Adversarial Examples Are Not Bugs, They Are Features
video: https://www.youtube.com/watch?v=AOZw1tgD8dA
available here: https://gradientscience.org/adv/
article: https://distill.pub/2019/advex-bugs-discussion/
video: https://www.youtube.com/watch?v=AOZw1tgD8dA
available here: https://gradientscience.org/adv/
article: https://distill.pub/2019/advex-bugs-discussion/
YouTube
Adversarial Attacks on Neural Networks - Bug or Feature?
❤️ Support us on Patreon: https://www.patreon.com/TwoMinutePapers
📝 The paper "Adversarial Examples Are Not Bugs, They Are Features" is available here:
https://gradientscience.org/adv/
The Distill discussion article is available here:
https://distill.pub/2019/advex…
📝 The paper "Adversarial Examples Are Not Bugs, They Are Features" is available here:
https://gradientscience.org/adv/
The Distill discussion article is available here:
https://distill.pub/2019/advex…
Continuous Delivery for Machine Learning
Automating the end-to-end lifecycle of Machine Learning applications
https://martinfowler.com/articles/cd4ml.html
Automating the end-to-end lifecycle of Machine Learning applications
https://martinfowler.com/articles/cd4ml.html
martinfowler.com
Continuous Delivery for Machine Learning
How to apply Continuous Delivery to build Machine Learning applications
Evolution of Representations in the Transformer
https://lena-voita.github.io/posts/emnlp19_evolution.html
https://lena-voita.github.io/posts/emnlp19_evolution.html
Teaching AI to plan using language in a new open-source strategy game
https://ai.facebook.com/blog/-teaching-ai-to-plan-using-language-in-a-new-open-source-strategy-game/
https://ai.facebook.com/blog/-teaching-ai-to-plan-using-language-in-a-new-open-source-strategy-game/
Facebook
Teaching AI to plan using language in a new open-source strategy game
Facebook AI has open sourced MiniRTSv2, a real-time strategy game designed to test and evaluate a range of AI techniques related to reinforcement learning, hierarchical decision-making and natural language processing.
An Inside Look at Flood Forecasting
https://ai.googleblog.com/2019/09/an-inside-look-at-flood-forecasting.html
Applying AI to some of the world’s biggest challenges
https://ai.google/social-good
https://ai.googleblog.com/2019/09/an-inside-look-at-flood-forecasting.html
Applying AI to some of the world’s biggest challenges
https://ai.google/social-good
blog.research.google
An Inside Look at Flood Forecasting
Self-driving Research in Review: CVPR 2019 Digest
https://medium.com/lyftlevel5/cvpr-digest-9195adbd5d0c
https://medium.com/lyftlevel5/cvpr-digest-9195adbd5d0c
Medium
Self-driving Research in Review: CVPR 2019 Digest
Peter Ondruska, Director, Research
Building AI to inform people's fashion choices
https://ai.facebook.com/blog/building-ai-to-inform-peoples-fashion-choice/
paper: https://research.fb.com/publications/fashion-minimal-edits-for-outfit-improvement/
https://ai.facebook.com/blog/building-ai-to-inform-peoples-fashion-choice/
paper: https://research.fb.com/publications/fashion-minimal-edits-for-outfit-improvement/
Facebook
Building AI to inform people's fashion choices
Facebook researchers have created an AI tool that analyzes sample images and then recommends easy changes to a person's outfit to make it more stylish.