3 citations · 10 across the 11 of their papers we have counts for
4 papers · 1 filter
Latent Space Editing in Transformer-Based Flow Matching
Vincent Tao Hu, David W Zhang, Pascal Mettes +3
This paper strives for image editing via generative models. Flow Matching is an emerging generative modeling technique that offers the advantage of simple and efficient training. S…
Data Augmentations in Deep Weight Spaces
Aviv Shamsian, David W. Zhang, Aviv Navon +10
Learning in weight spaces, where neural networks process the weights of other deep neural networks, has emerged as a promising research direction with applications in various field…
Robust Scheduling with GFlowNets
David W. Zhang, Corrado Rainone, Markus Peschl +1
Finding the best way to schedule operations in a computation graph is a classical NP-hard problem which is central to compiler optimization. However, evaluating the goodness of a s…
Unlocking Slot Attention by Changing Optimal Transport Costs
Yan Zhang, David W. Zhang, Simon Lacoste-Julien +2
Slot attention is a powerful method for object-centric modeling in images and videos. However, its set-equivariance limits its ability to handle videos with a dynamic number of obj…