Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Parnichkun, Rom N."'
Autor:
Parnichkun, Rom N., Massaroli, Stefano, Moro, Alessandro, Smith, Jimmy T. H., Hasani, Ramin, Lechner, Mathias, An, Qi, Ré, Christopher, Asama, Hajime, Ermon, Stefano, Suzuki, Taiji, Yamashita, Atsushi, Poli, Michael
We approach designing a state-space model for deep learning applications through its dual representation, the transfer function, and uncover a highly efficient sequence parallel inference algorithm that is state-free: unlike other proposed algorithms
Externí odkaz:
http://arxiv.org/abs/2405.06147
Autor:
Massaroli, Stefano, Poli, Michael, Fu, Daniel Y., Kumbong, Hermann, Parnichkun, Rom N., Timalsina, Aman, Romero, David W., McIntyre, Quinn, Chen, Beidi, Rudra, Atri, Zhang, Ce, Re, Christopher, Ermon, Stefano, Bengio, Yoshua
Recent advances in attention-free sequence models rely on convolutions as alternatives to the attention operator at the core of Transformers. In particular, long convolution sequence models have achieved state-of-the-art performance in many domains,
Externí odkaz:
http://arxiv.org/abs/2310.18780