61 citations · 150 across the 17 of their papers we have counts for
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cs.CV2023
Inferring Latent Class Statistics from Text for Robust Visual Few-Shot Learning
Yassir Bendou, Vincent Gripon, Bastien Pasdeloup +4
In the realm of few-shot learning, foundation models like CLIP have proven effective but exhibit limitations in cross-domain robustness especially in few-shot settings. Recent work…
cs.LG2023
DBsurf: A Discrepancy Based Method for Discrete Stochastic Gradient Estimation
Pau Mulet Arabi, Alec Flowers, Lukas Mauch +1
Computing gradients of an expectation with respect to the distributional parameters of a discrete distribution is a problem arising in many fields of science and engineering. Typic…
cs.LG2023
Efficient Training of Deep Equilibrium Models
Bac Nguyen, Lukas Mauch
Deep equilibrium models (DEQs) have proven to be very powerful for learning data representations. The idea is to replace traditional (explicit) feedforward neural networks with an…