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Found 7 papers, 3 papers with code
Spurious reconstruction from brain activity
However, text features alone are insufficient for mapping to the visual space.
On the Surrogate Gap between Contrastive and Supervised Losses
Recent theoretical studies have attempted to explain the benefit of the large negative sample size by upper-bounding the downstream classification loss with the contrastive loss.
Statistical Mechanical Analysis of Catastrophic Forgetting in Continual Learning with Teacher and Student Networks
Teacher-student learning is a framework in which we introduce two neural networks: one neural network is a target function in supervised learning, and the other is a learning neural network.
Role of two learning rates in convergence of model-agnostic meta-learning
Model-agnostic meta-learning (MAML) is known as a powerful meta-learning method.
Localized Generations with Deep Neural Networks for Multi-Scale Structured Datasets
The local learning approach extracts semantic representations for these datasets by training the embedding model from scratch for each local neighborhood, respectively.
A Wrapped Normal Distribution on Hyperbolic Space for Gradient-Based Learning
Hyperbolic space is a geometry that is known to be well-suited for representation learning of data with an underlying hierarchical structure.
Concept Formation and Dynamics of Repeated Inference in Deep Generative Models
Our study demonstrated that transient dynamics of inference first approaches a concept, and then moves close to a memory.
