Cody Marie WildinTowards Data ScienceA Search for Efficient Meta-Learning: MAMLs, Reptiles, and Related SpeciesIt’s an oft-lamented fact that the capabilities of modern machine learning tend to be narrow and brittle: while a given technique can be…22 min read·Sep 27, 2020--1--1
Cody Marie WildinTowards Data ScienceConditional Love: The Rise of Renormalization Techniques for Neural Network ConditioningConditional renormalization is an oft-unsung technique powering many recent ML successes; how does it work and where did the idea come…21 min read·Sep 8, 2019--2--2
Cody Marie WildinTowards Data ScienceIt’s Only Natural: An Excessively Deep Dive Into Natural Gradient OptimizationThis post gives an intuitive explanation of an approach called Natural Gradient, an elegant way to dynamically adjust gradient step size.15 min read·Mar 9, 2019--8--8
Cody Marie WildinTowards Data ScienceGenerating, With Style: The Mechanics Behind NVIDIA’s Highly Realistic GAN ImagesA new architecture, designed to leverage noise and allow for precise configuration of global features, is generating impressive results11 min read·Jan 21, 2019--1--1
Cody Marie WildinTowards Data ScienceA Tale of Two Convolutions: Differing Design Paradigms for Graph Neural Networks“Graph” is a one of those terms that’s fallen prey to natural language’s tendency to be less precise than its mathematical counterpart.14 min read·Dec 27, 2018--4--4
Cody Marie WildinTowards Data ScienceConvolution: An Exploration of a Familiar Operator’s Deeper RootsIn the world of modern machine learning, the convolution operator occupies the strange position: it’s both trivially familiar to anyone…10 min read·Oct 1, 2018--5--5
Cody Marie WildinTowards Data ScienceThe Pursuit of (Robotic) Happiness: How TRPO and PPO Stabilize Policy Gradient MethodsReinforcement Learning strikes me as the wild west of machine learning right now: a place full of drama and progress, with dreams of grand…16 min read·Jul 9, 2018--5--5
Cody Marie WildinTowards Data ScienceWith Great Power Comes Poor Latent Codes: Representation Learning in VAEs (Pt. 2)(If you haven’t done so yet, I recommend going back and reading Part 1 of this series on VAE failure modes; I spent more time there…14 min read·May 7, 2018--6--6
Cody Marie WildinTowards Data ScienceWhat a Disentangled Net We Weave: Representation Learning in VAEs (Pt. 1)It’s a truth universally acknowledged: that data not in possession of labels must be in want of unsupervised learning.15 min read·Apr 15, 2018--7--7
Cody Marie WildinTowards Data ScienceLearning About Algorithms That Learn to LearnThe premise of meta learning was an intoxicating one to me, when I first of heard it: the project of building machines that are not only…13 min read·Mar 24, 2018--2--2
