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Found 5 papers, 4 papers with code
Understanding LLMs Requires More Than Statistical Generalization
The last decade has seen blossoming research in deep learning theory attempting to answer, "Why does deep learning generalize?"
An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component Analysis
We investigate the relationship between system identification and intervention design in dynamical systems.
Embrace the Gap: VAEs Perform Independent Mechanism Analysis
Leveraging self-consistency, we show that the ELBO converges to a regularized log-likelihood.
Attention-based Curiosity-driven Exploration in Deep Reinforcement Learning
Reinforcement Learning enables to train an agent via interaction with the environment.
Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks
The aim of this paper is to introduce two widely applicable regularization methods based on the direct modification of weight matrices.
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