Important Note: This repository implements SVG-T2I, a text-to-image diffusion framework that performs visual generation directly in Visual Foundation Model (VFM) representation space, rather than ...
Abstract: Existing privacy protection methods primarily reduce sensitivity to training data by adding noise during the training process or constraining model attributes. These methods struggle to ...
VANCOUVER, British Columbia--(BUSINESS WIRE)--Variational AI, the company behind Enki™, an advanced foundation model for small molecule drug discovery, today ...
Merck & Co. has doubled down on its partnership with Variational AI, striking a deal worth up to $349 million to collaborate on small molecule candidates against two targets. Variational disclosed a ...
We introduce QFARE, a hybrid quantum-classical architecture for MNIST digit classification. Our approach employs a classical variational autoencoder (VAE) to compress 28×28 grayscale images into ...
Abstract: Variational autoencoders (VAEs) has been a popular generative model for its effectiveness, mathematical foundation, and its impact to other approaches in deep generative learning. For its ...
Variational Autoencoder (VAE) project using PyTorch, showcasing generative modeling through Fashion MNIST data encoding, decoding, and latent space exploration. Explore tasks like model implementation ...
This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms. All methods ...
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