Papers Shelf
A collection of some papers on various topics. Keeping an organized list helps in building mental models and quickly remembering the crux of the work.
Stochastic PDE’s
- How to solve the stochastic partial differential equation that gives a Matérn random field using the finite element method - Haakon Bakka (2018)
Distributional Regression
- Neural Additive Models: Interpretable Machine Learning with Neural Nets - Agarwal, R., Frosst, N., Zhang, X., Caruana, R., and Hinton, G. (2020)
- NAMLSS: Neural Additive Models for Location Scale and Shape - Thielmann, A., Kruse, R., Kneib, T., Safken, B. (2023)
- Generalized Additive Models for Location, Scale and Shape for High Dimensional Data—A Flexible Approach Based on Boosting - Andreas Mayr, Nora Fenske, Benjamin Hofner, Thomas Kneib, Matthias Schmid (2012)
- GAMLSS: Generalized Additive Models for Location Scale and Shape - D. Mikis Stasinopoulos, Robert A. Rigby (2007)
- Rage Against the Mean – A Review of Distributional Regression Approaches - Thomas Kneib, Alexander Silbersdorff, Benjamin Säfken (2023)
Black-Box Models
- NODE: Neural Oblivious Decision Ensembles - Popov S., Stanislav S., Babenko A. (2019)
Glass-Box Models
- NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning - C Chang, R Caruana, A Goldenberg (2021)
Regression
- A review and recommendations on variable selection methods in regression models for binary data - Souvik Bag, Kapil Gupta, Soudeep Deb
Variational Inference
- Variational Inference I - Course Notes (2011)
- A Stochastic Approximation Method - Robbins, H. and Monro, S. (1951)
- Variational Inference: A Review for Statisticians - Blei, D. M., Kucukelbir, A., McAuliffe, J. D. (2017)
Transformers
- Attention is All You Need - Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017)
- Tab-Transformer: Tabular Data Modeling Using Contextual Embeddings - Huang, X., Khetan, A., Cvitkovic, M., & Karnin, Z. (2020)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding - Devlin, Chang, Lee, Toutanova (2019)