Learning Transferable Visual Models From Natural Language Supervision
CLIP learns from image-caption pairs to recognize categories described in words.
2021
77,118
Works
Selected research papers and books, linked to their authors.
Going Deeper with Convolutions
GoogLeNet recognizes images with parallel filters operating at different scales.
2015
75,185
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Batch normalization rescales signals inside neural networks to speed up training.
2015
70,025
Latent Dirichlet Allocation
Discovers topics in document collections by treating each document as a mixture of themes.
2003
66,139
Dropout: A Simple Way to Prevent Neural Networks from Overfitting
Dropout reduces memorization by switching off parts of a neural network during training.
2014
66,007
Learning Internal Representations by Error Propagation
Explained how networks learn internal representations by passing errors backward through layers.
1986
62,699
Auto-Encoding Variational Bayes
Variational autoencoders learn compact representations of data to generate new examples.
2014
62,453
ImageNet Large Scale Visual Recognition Challenge
Documented ImageNet's shared tests and progress in recognizing and locating objects in images.
2015
57,636
Highly accurate protein structure prediction with AlphaFold
Presented AlphaFold 2, predicting proteins' three-dimensional shapes from their sequences.
2021
57,067
Efficient Estimation of Word Representations in Vector Space
Word2vec efficiently learns relationships between words from large text collections.
2013
56,905