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Daniel A. Abolafia

dblp:213/7595 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Probabilistic and Bayesian machine learning · 42% Deep learning architectures and training · 21% Trustworthy machine learning · 18%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Deep learning architectures and training › convolutional neural network
bayesian convolutional neural networks		 0.412019
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes · ICLR (Poster) 2019
Machine learning › Probabilistic and Bayesian machine learning › deep probabilistic models › bayesian deep learning
bayesian neural networks		 0.412019
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes · ICLR (Poster) 2019
Machine learning › Probabilistic and Bayesian machine learning › stochastic processes › gaussian process
neural network gaussian process		 0.412019
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes · ICLR (Poster) 2019
Machine learning › Learning theory
generalization		 0.312018
Sensitivity and Generalization in Neural Networks: an Empirical Study · ICLR (Poster) 2018
Machine learning › Trustworthy machine learning
robustness		 0.312018
Sensitivity and Generalization in Neural Networks: an Empirical Study · ICLR (Poster) 2018

Methods — techniques the papers use, named apart from their topics

gaussian process · 0.4bayesian inference · 0.4empirical study · 0.3
YearPublicationVenuePosition
2019 Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
Roman Novak, Lechao Xiao, Yasaman Bahri, Jaehoon Lee 0001, Greg Yang, Jiri Hron, Daniel A. Abolafia, Jeffrey Pennington, Jascha Sohl-Dickstein
 ICLR (Poster)7
2018 Sensitivity and Generalization in Neural Networks: an Empirical Study
Roman Novak, Yasaman Bahri, Daniel A. Abolafia, Jeffrey Pennington, Jascha Sohl-Dickstein
 ICLR (Poster)3