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Found 7 papers, 2 papers with code
cDVGAN: One Flexible Model for Multi-class Gravitational Wave Signal and Glitch Generation
Specifically, our experiments show that training convolutional neural networks (CNNs) with our cDVGAN-generated data improves the detection of samples embedded in detector noise beyond the synthetic data from other state-of-the-art GAN models.
DVGAN: Stabilize Wasserstein GAN training for time-domain Gravitational Wave physics
This paper presents a novel approach to simulating fixed-length time-domain signals using a three-player Wasserstein Generative Adversarial Network (WGAN), called DVGAN, that includes an auxiliary discriminator that discriminates on the derivatives of input signals.
Sim-Env: Decoupling OpenAI Gym Environments from Simulation Models
Reinforcement learning (RL) is one of the most active fields of AI research.
That looks interesting! Personalizing Communication and Segmentation with Random Forest Node Embeddings
We illustrate the algorithm's effectiveness for the classification task, and how it can be used to perform data mining tasks.
Monitoring Spatial Sustainable Development: semi-automated analysis of Satellite and Aerial Images for Energy Transition and Sustainability Indicators
The cross-site evaluation was furthermore carried out twice: deep learning models trained on he Netherlands were evaluated on Germany and vice versa.
Monitoring spatial sustainable development: Semi-automated analysis of satellite and aerial images for energy transition and sustainability indicators
As a matter of fact the quick adoption of solar panels by households is difficult to track, with local registries that miss a large number of the newly built solar panels.
Indexing the Event Calculus with Kd-trees to Monitor Diabetes
Personal Health Systems (PHS) are mobile solutions tailored to monitoring patients affected by chronic non communicable diseases.
