A.S. d'Avila Garcez

Artificial Intelligence · 1999–2020

A researcher in the Science corpus: 21 papers; trusts 289 researchers and is trusted by 39 researchers here, as inferred from the citation graph.

Subfields

Artificial Intelligence — 165 citations into it; #4,849 of 35,345 by trust here, #4,956 by citations
Computer Vision and Pattern Recognition — 64 citations into it; #14,157 of 21,575 by trust here, #14,822 by citations
Natural Language Processing — 49 citations into it
Model Architectures — 45 citations into it; #1,240 of 2,278 by trust here, #1,826 by citations
Probabilistic & Bayesian Methods — 36 citations into it
Computational Theory and Mathematics — 31 citations into it
Cognitive Neuroscience — 24 citations into it; #7,848 of 10,852 by trust here, #6,902 by citations
Knowledge Graphs & Representation — 18 citations into it; #93 of 226 by trust here, #102 by citations

Whom A.S. d'Avila Garcez trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

Who trusts A.S. d'Avila Garcez overall

Papers from A.S. d'Avila Garcez's perspective

Ordered by how strongly the researchers A.S. d'Avila Garcez trusts endorse each paper. Same corpus, a different order for every researcher.

ImageNet classification with deep convolutional neural networks
Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Long Short-Term Memory
Attention is All you Need (Neural Information Processing Systems)
Gradient-based learning applied to document recognition
ImageNet: A large-scale hierarchical image database
Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Learning Multiple Layers of Features from Tiny Images
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

Neurosymbolic AI: the 3rd wave (2020) — 562 citations
Deep Logic Networks: Inserting and Extracting Knowledge From Deep Belief Networks (2018) — 138 citations
Neural-Symbolic Cognitive Reasoning (2008) — 232 citations
Neural-symbolic learning systems - foundations and applications (2012) — 339 citations
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation (2017) — 472 citations
Learning and Representing Temporal Knowledge in Recurrent Networks (2011) — 50 citations
Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning (2019) — 392 citations
Sequence Classification Restricted Boltzmann Machines With Gated Units (2020) — 8 citations
Logic Tensor Networks (2020) — 365 citations
Learning and reasoning in logic tensor networks: theory and application to semantic image interpretation (2017) — 75 citations
Reasoning in Non-probabilistic Uncertainty: Logic Programming and Neural-Symbolic Computing as Examples (2017) — 25 citations
Logic Tensor Networks for Semantic Image Interpretation (2017) — 246 citations
Accuracy and Interpretability Trade-Offs in Machine Learning Applied to Safer Gambling (2016) — 30 citations
Tensor Networks : Deep Learning and Logical Reasoning from Data and Knowledge ⋆ (2016)
Neural-Symbolic Learning and Reasoning: Contributions and Challenges (2015) — 201 citations
Fast relational learning using bottom clause propositionalization with artificial neural networks (2013) — 138 citations
Knowledge Extraction from Deep Belief Networks for Images (2013)
A Connectionist Cognitive Model for Temporal Synchronisation and Learning (2007) — 26 citations
A Connectionist Computational Model for Epistemic and Temporal Reasoning (2006) — 31 citations
Reasoning about Time and Knowledge in Neural Symbolic Learning Systems (2003) — 38 citations