Research
 

Generative Models

All Work

Five ways IBM is using synthetic data to improve AI models
Five ways IBM is using synthetic data to improve AI models
IBM Research
↗
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
↗
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
↗
Generating new molecules with graph grammar
Generating new molecules with graph grammar
MIT News
↗
Breaking into the black box of artificial intelligence
Breaking into the black box of artificial intelligence
Nature
↗
When it comes to AI, can we ditch the datasets?
When it comes to AI, can we ditch the datasets?
MIT News
↗
Generative Ratio Matching Networks
Generative Ratio Matching Networks
Generative ModelsDeep Learning
 
A content-aware attack generator for AI cybersecurity
A content-aware attack generator for AI cybersecurity
Adversarial Machine LearningCybersecurity
 
Generative adversarial networks: What GANs are and how they’ve evolved
Generative adversarial networks: What GANs are and how they’ve evolved
VentureBeat
↗
SimVAE: Simulator-Assisted Training for Interpretable Generative Models
SimVAE: Simulator-Assisted Training for Interpretable Generative Models
Generative ModelsExplainability
 
Seeing What a GAN Cannot Generate
Seeing What a GAN Cannot Generate
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
↗
Teaching artificial intelligence to create visuals with more common sense
Teaching artificial intelligence to create visuals with more common sense
MIT News
↗
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
↗
Webby Awards: AI Portraits
Webby Awards: AI Portraits
Artsy
↗
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
Generative ModelsExplainability
 
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Generative ModelsGraph Deep Learning
 
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
Generative Models
 
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
Computer VisionGenerative Models