Thing is that Theorems 4 and 5 of arxiv.org/abs/2007.13505 ensure that the mHN type clustering is less of a potentially flaky snake oil move, but actually robust mathematically. As examples on real world data show, this type of pooling is effective.
A central mechanism in machine learning is to identify, store, and recognize patterns. How to learn, access, and retrieve such patterns is crucial in Hopfield networks and the more recent transformer ...
Nice question, thank you. I would suspect that classical clustering algorithms will be less effective compared to, say, "HopfieldPoolingLayers". The ultimate example of how effective mHNs are at MIL type problems is this: arxiv.org/abs/2007.13505
A central mechanism in machine learning is to identify, store, and recognize patterns. How to learn, access, and retrieve such patterns is crucial in Hopfield networks and the more recent transformer ...
Very nice read and highly recommended. Using contrastive learning and clustering via modern Hopfield Networks the state space for RL (or IRL) can be abstracted and reduced from data alone. x.com/gklambauer/s...
I mean ...
Did you hear about the tech industry banning the phrase "Irish Stew" from being a valid password? Apparently it isn't Stroganoff!
xLSTMs used to detect autism spectrum disorder (ASD) early, by being seemingly able to isolate relevant spatio-temporal upper body and head movement features when toddlers interact with parents. arxiv.org/abs/2408.16924
Autism Spectrum Disorder (ASD) is a rapidly growing neurodevelopmental disorder. Performing a timely intervention is crucial for the growth of young children with ASD, but traditional clinical...
xLSTMs seem to do well on audio data. arxiv.org/abs/2408.16568
While the transformer has emerged as the eminent neural architecture, several independent lines of research have emerged to address its limitations. Recurrent neural approaches have also observed...
Turns out simple xLSTMs do well at stock market predictions. Surprised so much I am not, but good to know. arxiv.org/abs/2408.12408
The stock market is a fundamental component of financial systems, reflecting economic health, providing investment opportunities, and influencing global dynamics. Accurate stock market predictions...
Very interesting results. xLSTMs works as a vision backbone - especially for large images (as could be expected). arxiv.org/abs/2406.04303
Fascinating read! Highly recommended. arxiv.org/abs/2405.08766
Out-of-distribution (OOD) detection is critical when deploying machine learning models in the real world. Outlier exposure methods, which incorporate auxiliary outlier data in the training...