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2411.04165
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Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences
6 November 2024
Niklas Schmidinger
Lisa Schneckenreiter
Philipp Seidl
Johannes Schimunek
Pieter-Jan Hoedt
Johannes Brandstetter
Andreas Mayr
Sohvi Luukkonen
Sepp Hochreiter
G. Klambauer
MedIm
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Papers citing
"Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences"
2 / 2 papers shown
Title
Tiled Flash Linear Attention: More Efficient Linear RNN and xLSTM Kernels
M. Beck
Korbinian Poppel
Phillip Lippe
Sepp Hochreiter
59
1
0
18 Mar 2025
A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks
Thomas Schmied
Thomas Adler
Vihang Patil
M. Beck
Korbinian Poppel
Johannes Brandstetter
G. Klambauer
Razvan Pascanu
Sepp Hochreiter
55
4
0
21 Feb 2025
1
