58 citations · 95 across the 8 of their papers we have counts for
8 papers
Domain Aligned CLIP for Few-shot Classification
Muhammad Waleed Gondal, Jochen Gast, Inigo Alonso Ruiz +4
Large vision-language representation learning models like CLIP have demonstrated impressive performance for zero-shot transfer to downstream tasks while largely benefiting from int…
Dynamic Inference with Neural Interpreters
Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi +4
Modern neural network architectures can leverage large amounts of data to generalize well within the training distribution. However, they are less capable of systematic generalizat…
Function Contrastive Learning of Transferable Meta-Representations
Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman +3
Meta-learning algorithms adapt quickly to new tasks that are drawn from the same task distribution as the training tasks. The mechanism leading to fast adaptation is the conditioni…
S2RMs: Spatially Structured Recurrent Modules
Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal +5
Capturing the structure of a data-generating process by means of appropriate inductive biases can help in learning models that generalize well and are robust to changes in the inpu…
Disentangled State Space Representations
Đorđe Miladinović, Muhammad Waleed Gondal, Bernhard Schölkopf +2
Sequential data often originates from diverse domains across which statistical regularities and domain specifics exist. To specifically learn cross-domain sequence representations,…
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset
Muhammad Waleed Gondal, Manuel Wüthrich, Đorđe Miladinović +7
Learning meaningful and compact representations with disentangled semantic aspects is considered to be of key importance in representation learning. Since real-world data is notori…
Kernel Mean Matching for Content Addressability of GANs
Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal +3
We propose a novel procedure which adds "content-addressability" to any given unconditional implicit model e.g., a generative adversarial network (GAN). The procedure allows users…
The Unreasonable Effectiveness of Texture Transfer for Single Image Super-resolution
Muhammad Waleed Gondal, Bernhard Schölkopf, Michael Hirsch
While implicit generative models such as GANs have shown impressive results in high quality image reconstruction and manipulation using a combination of various losses, we consider…