John F. Canny
University of California, Berkeley
Professor
Department of Electrical Engineering and Computer Sciences
Research Area
#Computer science#Artificial intelligence#Machine learning#Human-computer interaction#Artificial neural network#Visualization#Key (cryptography)#World Wide Web#Multimedia#Code (cryptography)
SCIE paper information
Papers relevant to ‘Computer science’: 3
Research performance of SCIE papers matching with ‘Computer science’
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
GPU accelerated t-distributed stochastic neighbor embedding
2019/09 JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2.296 Impact Factor 18 citations
Subsemble: an ensemble method for combining subset-specific algorithm fits
2014/04 JOURNAL OF APPLIED STATISTICS 0.417 Impact Factor 10 citations
Papers for author ‘John F. Canny’: 3
Number of published SCIE papers by year
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
GPU accelerated t-distributed stochastic neighbor embedding
2019/09 JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2.296 Impact Factor 18 citations
Subsemble: an ensemble method for combining subset-specific algorithm fits
2014/04 JOURNAL OF APPLIED STATISTICS 0.417 Impact Factor 10 citations
conference information
Papers relevant to ‘Computer science’: 11
Research performance of Top-tier Conference matching with ‘Computer science’
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
Interpretable Learning for Self-Driving Cars by Visualizing Causal Attention
2017/03 ICCV Top-tier Conference 147 citations
Textual Explanations for Self-Driving Vehicles
2018/09 ECCV Top-tier Conference 80 citations
Papers for author ‘John F. Canny’: 14
Number of published Top-tier Conference by year
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
Evaluating Protein Transfer Learning with TAPE.
2019/12 NEURIPS Top-tier Conference 150 citations
Interpretable Learning for Self-Driving Cars by Visualizing Causal Attention
2017/03 ICCV Top-tier Conference 147 citations
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