DONUT: Database of Original & Non-Theoretical Uses of Topology Home • Papers • Software • Tags • FAQ • Contributors 🍩 Database of Original & Non-Theoretical Uses of Topology Search I'm Feeling Lucky (found 13 matches in 0.001929s) Simplicial Neural Networks (2020) Stefania Ebli , Michaël Defferrard , Gard Spreemann Abstract We present simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called simplicial complexes
Deep neural networks, empowered by pre-trained language models, have achieved remarkable results in natural language understanding (NLU) tasks. However, their performances can drastically deteriorate when logical reasoning is needed. This is because NLU in principle depends on not only analogical reasoning, which deep neural networks are good at, but also logical reasoning. According to the dual-process theory, analogical reasoning and logical reasoning are respectively carried out by System 1 and System 2
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With limited data, simple models often generalize better than deep networks. We compare both on a small classification task
Explore how Instruction Set Architecture (ISA) shapes neural network inference, affecting performance, efficiency, and local execution for AI tasks
Learn about the Bayesian Networks (BNs
#### 24 Results Wed 2:30 The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks Blake Bordelon ⋅ Cengiz Pehlevan Wed 1:50 The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks Blake Bordelon ⋅ Cengiz Pehlevan Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics Sirui Zheng ⋅ Lingxiao Wang ⋅ Shuang Qiu ⋅ Zuyue Fu ⋅ Zhuoran Yang ⋅ Csaba Szepesvari ⋅ Zhaoran Wang Tue 7:30 Neural
Keras documentation: Classification with Neural Decision Forests
Artificial Neural Network Market size is expected to grow at a CAGR of 18.91% from 2022 to 2035, Market Analysis by Type & Component
Andrew Gibiansky :: Math → [Code] Check out Kronos Notebook , my new IPython -based Mac app for interactive computing and data analysis in Python or Haskell. --> NRAM: Neural Random Access Memory Saturday, June 4, 2016 In previous posts, we started with basic neural network architectures ( multilayer perceptrons ) and then continued with specialized architectures for image recognition and object classification ( convolutional networks ), sequence learning ( recurrent networks ), and speech recognition