Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Tatro, N. Joseph"'
We propose a novel algorithm, Salient Conditional Diffusion (Sancdifi), a state-of-the-art defense against backdoor attacks. Sancdifi uses a denoising diffusion probabilistic model (DDPM) to degrade an image with noise and then recover said image usi
Externí odkaz:
http://arxiv.org/abs/2301.13862
Massive molecular simulations of drug-target proteins have been used as a tool to understand disease mechanism and develop therapeutics. This work focuses on learning a generative neural network on a structural ensemble of a drug-target protein, e.g.
Externí odkaz:
http://arxiv.org/abs/2205.10423
Publikováno v:
Advances in Neural Information Processing Systems, Volume 33, 2020
The loss landscapes of deep neural networks are not well understood due to their high nonconvexity. Empirically, the local minima of these loss functions can be connected by a learned curve in model space, along which the loss remains nearly constant
Externí odkaz:
http://arxiv.org/abs/2009.02439
Geometric disentanglement, the separation of latent codes for intrinsic (i.e. identity) and extrinsic(i.e. pose) geometry, is a prominent task for generative models of non-Euclidean data such as 3D deformable models. It provides greater interpretabil
Externí odkaz:
http://arxiv.org/abs/2005.11622
Autor:
Yinzhu Jin, McDaniel, Rory, Tatro, N. Joseph, Catanzaro, Michael J., Smith, Abraham D., Bendich, Paul, Dwyer, Matthew B., Fletcher, P. Thomas
Publikováno v:
Frontiers in Computer Science; 2024, p1-15, 15p
