Generative Models
All Work
How to Detect AI-Generated Text, According to Researchers
How to Detect AI-Generated Text, According to Researchers
WIRED
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3 Questions: Innovation in financial services through synthetic data
3 Questions: Innovation in financial services through synthetic data
MIT-IBM Watson AI Lab
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Five ways IBM is using synthetic data to improve AI models
Five ways IBM is using synthetic data to improve AI models
IBM Research
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Perceptron: AI that sees with sound, learns to walk and predicts seismic physics
Perceptron: AI that sees with sound, learns to walk and predicts seismic physics
TechCrunch
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How to use AI to discover new drugs and materials with limited data
How to use AI to discover new drugs and materials with limited data
IBM Research
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Generating new molecules with graph grammar
Generating new molecules with graph grammar
MIT News
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Breaking into the black box of artificial intelligence
Breaking into the black box of artificial intelligence
Nature
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When it comes to AI, can we ditch the datasets?
When it comes to AI, can we ditch the datasets?
MIT News
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Generative adversarial networks: What GANs are and how they’ve evolved
Generative adversarial networks: What GANs are and how they’ve evolved
VentureBeat
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SimVAE: Simulator-Assisted Training for Interpretable Generative Models
SimVAE: Simulator-Assisted Training for Interpretable Generative Models
MIT and IBM’s new A.I. image-editing tool lets you paint with neurons
MIT and IBM’s new A.I. image-editing tool lets you paint with neurons
Digital Trends
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Teaching artificial intelligence to create visuals with more common sense
Teaching artificial intelligence to create visuals with more common sense
MIT News
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GAN Paint Studio uses AI to add, delete, and modify objects in photos
GAN Paint Studio uses AI to add, delete, and modify objects in photos
Venture Beat
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Webby Awards: AI Portraits
Webby Awards: AI Portraits
Artsy
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GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation
Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation