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Found 5 papers, 2 papers with code
Learning to Focus: Cascaded Feature Matching Network for Few-shot Image Recognition
By applying the proposed feature matching block in different layers of the few-shot recognition network, multi-scale information among the compared images can be incorporated into the final cascaded matching feature, which boosts the recognition performance further and generalizes better by learning on relationships.
Diversity Transfer Network for Few-Shot Learning
The learning problem of the sample generation (i. e., diversity transfer) is solved via minimizing an effective meta-classification loss in a single-stage network, instead of the generative loss in previous works.
Combining docking pose rank and structure with deep learning improves protein-ligand binding mode prediction
We develop a deep learning model for binding mode prediction that uses docking ranking as input in combination with docking structures.
Natural Language Inference over Interaction Space
Natural Language Inference (NLI) task requires an agent to determine the logical relationship between a natural language premise and a natural language hypothesis.
Ranked #12 on
Paraphrase Identification
on Quora Question Pairs
(Accuracy metric)
Deep Tempering
Restricted Boltzmann Machines (RBMs) are one of the fundamental building blocks of deep learning.
