#deepnetworks — Public Fediverse posts

Is it right to basically juxtapose #deepNetworks against #knowledgeBasedReasoning ?
Eg. Hopfield nets versus case based reasoning.

Where deep networks generally simulate parts of biological mechanisms, often on very fast/hungry hardware very quickly, often involving Hidden Layers for what's-actually-being-done.

Whereas in knowledge based reasoning, high level descriptions of the world are being reasoned about eg as cases, (+ situation calculus say). Decision trees.

Is it right to basically juxtapose #deepNetworks against #knowledgeBasedReasoning ?
Eg. Hopfield nets versus case based reasoning.

Where deep networks generally simulate parts of biological mechanisms, often on very fast/hungry hardware very quickly, often involving Hidden Layers for what's-actually-being-done.

Whereas in knowledge based reasoning, high level descriptions of the world are being reasoned about eg as cases, (+ situation calculus say). Decision trees.

Is it right to basically juxtapose #deepNetworks against #knowledgeBasedReasoning ?
Eg. Hopfield nets versus case based reasoning.

Where deep networks generally simulate parts of biological mechanisms, often on very fast/hungry hardware very quickly, often involving Hidden Layers for what's-actually-being-done.

Whereas in knowledge based reasoning, high level descriptions of the world are being reasoned about eg as cases, (+ situation calculus say). Decision trees.

Is it right to basically juxtapose #deepNetworks against #knowledgeBasedReasoning ?
Eg. Hopfield nets versus case based reasoning.

Where deep networks generally simulate parts of biological mechanisms, often on very fast/hungry hardware very quickly, often involving Hidden Layers for what's-actually-being-done.

Whereas in knowledge based reasoning, high level descriptions of the world are being reasoned about eg as cases, (+ situation calculus say). Decision trees.

Efficient optimization of deep neural quantum states toward machine precision

Neural quantum states have emerged as a novel promising numerical method to solve the quantum many-body problem. However, it has remained a key challenge to train modern large-scale deep network architectures, which would be vital in utilizing the full power of the underlying artificial neural networks. In this recent preprint we take on this challenge:

https://arxiv.org/abs/2302.01941

#nqs #quantum #deepnetworks

Efficient optimization of deep neural quantum states toward machine precision

Neural quantum states have emerged as a novel promising numerical method to solve the quantum many-body problem. However, it has remained a key challenge to train modern large-scale deep network architectures, which would be vital in utilizing the full power of the underlying artificial neural networks. In this recent preprint we take on this challenge:

https://arxiv.org/abs/2302.01941

#nqs #quantum #deepnetworks

Efficient optimization of deep neural quantum states toward machine precision

Neural quantum states have emerged as a novel promising numerical method to solve the quantum many-body problem. However, it has remained a key challenge to train modern large-scale deep network architectures, which would be vital in utilizing the full power of the underlying artificial neural networks. In this recent preprint we take on this challenge:

https://arxiv.org/abs/2302.01941

#nqs #quantum #deepnetworks

Efficient optimization of deep neural quantum states toward machine precision

Neural quantum states have emerged as a novel promising numerical method to solve the quantum many-body problem. However, it has remained a key challenge to train modern large-scale deep network architectures, which would be vital in utilizing the full power of the underlying artificial neural networks. In this recent preprint we take on this challenge:

https://arxiv.org/abs/2302.01941

#nqs #quantum #deepnetworks

#CommonLisp #Gopher #binryhop #deepNetworks #asdf #lisp
gopher://tilde.institute/1/~screwtape/binry-hop/
https://gopher.floodgap.com/gopher/gw.lite?=tilde.institute+70+312f7e7363726577746170652f62696e72792d686f702f
gopher://gopher.club/1/users/screwtape/
https://gopher.floodgap.com/gopher/gw.lite?=gopher.club+70+312f75736572732f7363726577746170652f

I was redeveloping my nascent binry-hop deep hopfield network package to use package-inferred-system, so different sorts of components and data (book)? can be cooked into one overarching system but loaded separately.

I'm happy with it; and I believe in using asdf strongly idiomatically. Commentary?

#CommonLisp #Gopher #binryhop #deepNetworks #asdf #lisp
gopher://tilde.institute/1/~screwtape/binry-hop/
https://gopher.floodgap.com/gopher/gw.lite?=tilde.institute+70+312f7e7363726577746170652f62696e72792d686f702f
gopher://gopher.club/1/users/screwtape/
https://gopher.floodgap.com/gopher/gw.lite?=gopher.club+70+312f75736572732f7363726577746170652f

I was redeveloping my nascent binry-hop deep hopfield network package to use package-inferred-system, so different sorts of components and data (book)? can be cooked into one overarching system but loaded separately.

I'm happy with it; and I believe in using asdf strongly idiomatically. Commentary?

#CommonLisp #Gopher #binryhop #deepNetworks #asdf #lisp
gopher://tilde.institute/1/~screwtape/binry-hop/
https://gopher.floodgap.com/gopher/gw.lite?=tilde.institute+70+312f7e7363726577746170652f62696e72792d686f702f
gopher://gopher.club/1/users/screwtape/
https://gopher.floodgap.com/gopher/gw.lite?=gopher.club+70+312f75736572732f7363726577746170652f

I was redeveloping my nascent binry-hop deep hopfield network package to use package-inferred-system, so different sorts of components and data (book)? can be cooked into one overarching system but loaded separately.

I'm happy with it; and I believe in using asdf strongly idiomatically. Commentary?