Lorenzo Loconte
@loreloc.bsky.social
#probabilistic-ml #circuits #tensor-networks
PhD student @ University of Edinburgh
https://loreloc.github.io/
PhD student @ University of Edinburgh
https://loreloc.github.io/
The last speaker of the workshop is Alexandros Georgiou, who is giving an introduction to polynomial networks and equivariant tensor network architecture, as well as how to implement them.
March 4, 2025 at 8:45 PM
The last speaker of the workshop is Alexandros Georgiou, who is giving an introduction to polynomial networks and equivariant tensor network architecture, as well as how to implement them.
After lunch break, Andrew G. Wilson (@andrewgwils.bsky.social) is now giving his presentation on the importance of linear algebra structures in ML, as well as on how to navigate such structures in practice.
March 4, 2025 at 7:36 PM
After lunch break, Andrew G. Wilson (@andrewgwils.bsky.social) is now giving his presentation on the importance of linear algebra structures in ML, as well as on how to navigate such structures in practice.
After Nadav it is now the turn of Guillaume Rabusseau, who is joining us online
Guillaume guides us through interesting expressiveness relationships of families of RNNs that are parameterized through tensor factorizations techniques
Guillaume guides us through interesting expressiveness relationships of families of RNNs that are parameterized through tensor factorizations techniques
March 4, 2025 at 5:05 PM
After Nadav it is now the turn of Guillaume Rabusseau, who is joining us online
Guillaume guides us through interesting expressiveness relationships of families of RNNs that are parameterized through tensor factorizations techniques
Guillaume guides us through interesting expressiveness relationships of families of RNNs that are parameterized through tensor factorizations techniques
Live from the CoLoRAI workshop at AAAI
(april-tools.github.io/colorai/)
Nadav Cohen is now giving his talk on "What Makes Data Suitable for Deep Learning?"
Tools from quantum physics are shown to be useful in building more expressive deep learning models by changing the data distribution.
(april-tools.github.io/colorai/)
Nadav Cohen is now giving his talk on "What Makes Data Suitable for Deep Learning?"
Tools from quantum physics are shown to be useful in building more expressive deep learning models by changing the data distribution.
March 4, 2025 at 2:54 PM
Live from the CoLoRAI workshop at AAAI
(april-tools.github.io/colorai/)
Nadav Cohen is now giving his talk on "What Makes Data Suitable for Deep Learning?"
Tools from quantum physics are shown to be useful in building more expressive deep learning models by changing the data distribution.
(april-tools.github.io/colorai/)
Nadav Cohen is now giving his talk on "What Makes Data Suitable for Deep Learning?"
Tools from quantum physics are shown to be useful in building more expressive deep learning models by changing the data distribution.
We are going to present our poster "Sum of Squares Circuits" at AAAI in Philadelphia today
Hall E 12:30pm-14:00pm poster #840
We trace expressiveness connections of different types of additive and subtractive deep mixture models and tensor networks
📜 arxiv.org/abs/2408.11778
Hall E 12:30pm-14:00pm poster #840
We trace expressiveness connections of different types of additive and subtractive deep mixture models and tensor networks
📜 arxiv.org/abs/2408.11778
February 27, 2025 at 12:59 PM
We are going to present our poster "Sum of Squares Circuits" at AAAI in Philadelphia today
Hall E 12:30pm-14:00pm poster #840
We trace expressiveness connections of different types of additive and subtractive deep mixture models and tensor networks
📜 arxiv.org/abs/2408.11778
Hall E 12:30pm-14:00pm poster #840
We trace expressiveness connections of different types of additive and subtractive deep mixture models and tensor networks
📜 arxiv.org/abs/2408.11778