Arash Vahdat – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-01-23T19:54:29Z http://www.open-lab.net/blog/feed/ Arash Vahdat <![CDATA[Evaluating GenMol as a Generalist Foundation Model for Molecular Generation]]> http://www.open-lab.net/blog/?p=94836 2025-01-23T19:54:29Z 2025-01-13T14:00:00Z Traditional computational drug discovery relies almost exclusively on highly task-specific computational models for hit identification and lead optimization....]]>

Traditional computational drug discovery relies almost exclusively on highly task-specific computational models for hit identification and lead optimization. Adapting these specialized models to new tasks requires substantial time, computational power, and expertise—challenges that grow when researchers simultaneously work across multiple targets or properties.

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Arash Vahdat <![CDATA[Enhance Text-to-Image Fine-Tuning with DRaFT+, Now Part of NVIDIA NeMo]]> http://www.open-lab.net/blog/?p=81405 2024-05-02T19:07:04Z 2024-04-26T14:00:00Z Text-to-image diffusion models have been established as a powerful method for high-fidelity image generation based on given text. Nevertheless, diffusion models...]]>

Text-to-image diffusion models have been established as a powerful method for high-fidelity image generation based on given text. Nevertheless, diffusion models do not always grant the desired alignment between the given input text and the generated image, especially for complicated idiosyncratic prompts that are not encountered in real life. Hence, there is growing interest in efficiently fine…

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Arash Vahdat <![CDATA[Improving Diffusion Models as an Alternative To GANs, Part 2]]> http://www.open-lab.net/blog/?p=46193 2022-12-14T16:06:33Z 2022-04-26T18:51:00Z This is part of a series on how researchers at NVIDIA have developed methods to improve and accelerate sampling from diffusion models, a novel and powerful...]]>

This is part of a series on how researchers at NVIDIA have developed methods to improve and accelerate sampling from diffusion models, a novel and powerful class of generative models. Part 1 introduced diffusion models as a powerful class for deep generative models and examined their trade-offs in addressing the generative learning trilemma. While diffusion models satisfy both the first and…

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Arash Vahdat <![CDATA[Improving Diffusion Models as an Alternative To GANs, Part 1]]> http://www.open-lab.net/blog/?p=46191 2023-06-12T20:52:31Z 2022-04-26T18:50:00Z This is part of a series on how NVIDIA researchers have developed methods to improve and accelerate sampling from diffusion models, a novel and powerful class...]]>

This is part of a series on how NVIDIA researchers have developed methods to improve and accelerate sampling from diffusion models, a novel and powerful class of generative models. Part 2 covers three new techniques for overcoming the slow sampling challenge in diffusion models. Generative models are a class of machine learning methods that learn a representation of the data they are trained…

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Arash Vahdat <![CDATA[Discovering GPU-friendly Deep Neural Networks with Unified Neural Architecture Search]]> http://www.open-lab.net/blog/?p=21847 2022-08-21T23:40:45Z 2020-11-05T21:29:02Z After the first successes of deep learning, designing neural network architectures with desirable performance criteria for a given task (for example, high...]]>

After the first successes of deep learning, designing neural network architectures with desirable performance criteria for a given task (for example, high accuracy or low latency) has been a challenging problem. Some call it alchemy and some intuition, but the task of discovering a novel architecture often involves a tedious and costly trial-and-error process of searching in an exponentially large…

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