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Found 3 papers, 2 papers with code
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
State-space models (SSMs), such as Mamba (Gu & Dao, 2023), have been proposed as alternatives to Transformer networks in language modeling, by incorporating gating, convolutions, and input-dependent token selection to mitigate the quadratic cost of multi-head attention.
Strong Lottery Ticket Hypothesis with $\varepsilon$--perturbation
The strong Lottery Ticket Hypothesis (LTH) claims the existence of a subnetwork in a sufficiently large, randomly initialized neural network that approximates some target neural network without the need of training.
Frame Difference-Based Temporal Loss for Video Stylization
To ensure temporal inconsistency between the frames of the stylized video, a common approach is to estimate the optic flow of the pixels in the original video and make the generated pixels match the estimated optical flow.
