- A Type-theoretic Reconstruction of the Visitor Pattern by Peter Buchlovsky and Hayo Thielecke
- The VISITOR Pattern as a Reusable, Generic, Type-Safe Component by Bruno C. d. S. Oliveira, Meng Wang, and Jeremy Gibbons
- Scala and the visitor pattern by Travis Brown and a reddit discussion
- Visitor Pattern, Catamorphism and Algebraic Data Type by Alexandre Bertails
- Modular domain-specific language components in scala by Christian Hofer and Klaus Ostermann
- Towards improved GADT reasoning in Scala by EPFL
- EVF: An Extensible and Expressive Visitor Framework for Programming Language Reuse by Weixin Zhang and Bruno C. d. S. Oliveira
- What is an Adjunction? Part 1 (Motivation) by @math3ma
- What is an Adjunction? Part 2 (Definition) by @math3ma
- The Power of Adjunctions by Bartosz Milewski
- An Adjunction That Induces the Reader Monad by Runar
- Adjunctions in everyday life by Runar
- Adjunctions in everyday life by Runar
- Relational Algebra by way of Adjunctions by Jeremy Gibbons et al ..
- Adjunctions in the wild : foldl
- Generic Deriving of Generic Traversals
- Tweet link
- Digging into Lenses
- Optics by Example - a book by Chris Penner
- Categories of Optics
- Profunctor Optics and Yoneda Lemma
- Profunctor Optics: Modular Data Access
- Relational Algebra with Fancy Types
- Profunctors as Relations
- Promonads, Arrows, and Einstein Notation for Profunctors
- Profunctors in Haskell
- Addressing Pieces of State with Profunctors
- Lenses that work with Arrows
- Profunctor Optics - A Categorical Update
- Time Series Anomaly Detection with Variational Autoencoders by Chunkai Zhang, Yingyang Chen
- Visualizing and Measuring the Geometry of BERT by Andy Coenen, Emily Reif, Ann Yuan, Been Kim, Adam Pearce, Fernanda Viégas, Martin Wattenberg
- Language, trees, and geometry in neural networks
- Language, Context, and Geometry in Neural Networks
- Monte Carlo Gradient Estimation in Machine Learning by Shakir Mohamed, Mihaela Rosca, Michael Figurnov, Andriy Mnih
- Attention and Augmented Recurrent Neural Networks
- Deep AutoRegressive Networks
- Neural Transfer Learning for Natural Language Processing
- On Statistical Thinking in Deep Learning
- Stochastic Backpropagation and Approximate Inference in Deep Generative Models by Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra