Controllable Generation is a machine learning approach that enables the guided creation of data, content, or structures with specified properties or constraints. It is commonly used in generative models such as diffusion models, variational autoencoders, and large language models, where users can influence outputs through conditioning variables, prompts, or latent controls. This approach supports applications such as molecular design, image synthesis, and text generation, allowing precise control over characteristics while maintaining realism and coherence.
Designing drug molecules is no longer just about generation, but control. NEC Laboratories America introduces MolDiffdAE, a diffusion-based framework that enables precise, multi-objective tuning of 3D molecular properties. By learning a semantic space, researchers can efficiently guide design, accelerating drug discovery and exploration of chemical space.
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NEC Laboratories America, Inc. (NEC Labs) is the US-based center for NEC Corporation’s global network of corporate research laboratories. Our diverse research groups collaborate with industry, academia and governments to provide disruptive solutions to complex problems. A leader in the integration of IT and network technologies with more than 100 years of expertise, NEC provides a combination of products and solutions that cross-utilize the company’s experience and global resources to meet the complex and ever-changing needs of its customers.