8 citations · 16 across the 4 of their papers we have counts for
4 papers
Analysis of Catastrophic Forgetting for Random Orthogonal Transformation Tasks in the Overparameterized Regime
Daniel Goldfarb, Paul Hand
Overparameterization is known to permit strong generalization performance in neural networks. In this work, we provide an initial theoretical analysis of its effect on catastrophic…
Causal Inference via Conditional Kolmogorov Complexity using MDL Binning
Daniel Goldfarb, Scott Evans
Recent developments have linked causal inference with Algorithmic Information Theory, and methods have been developed that utilize Conditional Kolmogorov Complexity to determine ca…
Understanding Deep Neural Networks Using Topological Data Analysis
Daniel Goldfarb
Deep neural networks (DNN) are black box algorithms. They are trained using a gradient descent back propagation technique which trains weights in each layer for the sole goal of mi…
An Application of Topological Data Analysis to Hockey Analytics
Daniel Goldfarb
This paper applies the major computational tool from Topological Data Analysis (TDA), persistent homology, to discover patterns in the data related to professional sports teams. I…