Under License Creative Commons Attribution 4.0 International

Previous publications

1. I'm supposed to present 'Conformal Predictive Simulations for Univariate Time Series' at COPA CONFERENCE 2025 in London... Sep 4, 2025
2. external regressors in ahead::dynrmf's interface for Machine learning forecasting Sep 1, 2025
3. Another interesting decision, now for 'Beyond Nelson-Siegel and splines: A model-agnostic Machine Learning framework for discount curve calibration, interpolation and extrapolation' Aug 20, 2025
4. Boosting any randomized based learner for regression, classification and univariate/multivariate time series forcasting Jul 26, 2025
5. New nnetsauce version with CustomBackPropRegressor (CustomRegressor with Backpropagation) and ElasticNet2Regressor (Ridge2 with ElasticNet regularization) Jul 15, 2025
6. mlsauce (home to a model-agnostic gradient boosting algorithm) can now be installed from PyPI. Jul 10, 2025
7. A user-friendly graphical interface to techtonique dot net's API (will eventually contain graphics). Jul 8, 2025
8. Calling =TECHTO_MLCLASSIFICATION for Machine Learning supervised CLASSIFICATION in Excel is just a matter of copying and pasting Jul 7, 2025
9. Calling =TECHTO_MLREGRESSION for Machine Learning supervised regression in Excel is just a matter of copying and pasting Jul 6, 2025
10. Calling =TECHTO_RESERVING and =TECHTO_MLRESERVING for claims triangle reserving in Excel is just a matter of copying and pasting Jul 5, 2025
11. Calling =TECHTO_SURVIVAL for Survival Analysis in Excel is just a matter of copying and pasting Jul 4, 2025
12. Calling =TECHTO_SIMULATION for Stochastic Simulation in Excel is just a matter of copying and pasting Jul 3, 2025
13. Calling =TECHTO_FORECAST for forecasting in Excel is just a matter of copying and pasting Jul 2, 2025
14. Random Vector Functional Link (RVFL) artificial neural network with 2 regularization parameters successfully used for forecasting/synthetic simulation in professional settings: Extensions (including Bayesian) Jul 1, 2025
15. R version of 'Backpropagating quasi-randomized neural networks' Jun 24, 2025
16. Backpropagating quasi-randomized neural networks Jun 23, 2025
17. Beyond ARMA-GARCH: leveraging any statistical model for volatility forecasting Jun 21, 2025
18. Stacked generalization (Machine Learning model stacking) + conformal prediction for forecasting with ahead::mlf Jun 18, 2025
19. An Overfitting dilemma: XGBoost Default Hyperparameters vs GenericBooster + LinearRegression Default Hyperparameters Jun 14, 2025
20. Programming language-agnostic reserving using RidgeCV, LightGBM, XGBoost, and ExtraTrees Machine Learning models Jun 13, 2025
21. Exceptionally, and on a more personal note (otherwise I may get buried alive)... Jun 10, 2025
22. Free R, Python and SQL editors in techtonique dot net Jun 9, 2025
23. Beyond Nelson-Siegel and splines: A model-agnostic Machine Learning framework for discount curve calibration, interpolation and extrapolation Jun 7, 2025
24. scikit-learn, glmnet, xgboost, lightgbm, pytorch, keras, nnetsauce in probabilistic Machine Learning (for longitudinal data) Reserving (work in progress) Jun 6, 2025
25. R version of Probabilistic Machine Learning (for longitudinal data) Reserving (work in progress) Jun 5, 2025
26. Probabilistic Machine Learning (for longitudinal data) Reserving (work in progress) Jun 4, 2025
27. Python version of Beyond ARMA-GARCH: leveraging model-agnostic Quasi-Randomized networks and conformal prediction for nonparametric probabilistic stock forecasting (ML-ARCH) Jun 3, 2025
28. Beyond ARMA-GARCH: leveraging model-agnostic Machine Learning and conformal prediction for nonparametric probabilistic stock forecasting (ML-ARCH) Jun 2, 2025
29. Permutations and SHAPley values for feature importance in techtonique dot net's API (with R + Python + the command line) Jun 1, 2025
30. Which patient is going to survive longer? Another guide to using techtonique dot net's API (with R + Python + the command line) for survival analysis May 31, 2025
31. A Guide to Using techtonique.net's API and rush for simulating and plotting Stochastic Scenarios May 30, 2025
32. Simulating Stochastic Scenarios with Diffusion Models: A Guide to Using techtonique.net's API for the purpose May 29, 2025
33. Will my apartment in 5th avenue be overpriced or not? Harnessing the power of www.techtonique.net (+ xgboost, lightgbm, catboost) to find out May 28, 2025
34. How long must I wait until something happens: A Comprehensive Guide to Survival Analysis via an API May 27, 2025
35. Harnessing the Power of techtonique.net: A Comprehensive Guide to Machine Learning Classification via an API May 26, 2025
36. Quantile regression with any regressor -- Examples with RandomForestRegressor, RidgeCV, KNeighborsRegressor May 20, 2025
37. Survival stacking: survival analysis translated as supervised classification in R and Python May 5, 2025
38. 'Bayesian' optimization of hyperparameters in a R machine learning model using the bayesianrvfl package Apr 25, 2025
39. A lightweight interface to scikit-learn in R: Bayesian and Conformal prediction Apr 21, 2025
40. A lightweight interface to scikit-learn in R Pt.2: probabilistic time series forecasting in conjunction with ahead::dynrmf Apr 20, 2025
41. Extending the Theta forecasting method to GLMs, GAMs, GLMBOOST and attention: benchmarking on Tourism, M1, M3 and M4 competition data sets (28000 series) Apr 14, 2025
42. Extending the Theta forecasting method to GLMs and attention Apr 8, 2025
43. Nonlinear conformalized Generalized Linear Models (GLMs) with R package 'rvfl' (and other models) Mar 31, 2025
44. Probabilistic Time Series Forecasting (predictive simulations) in Microsoft Excel using Python, xlwings lite and www.techtonique.net Mar 28, 2025
45. Conformalize (improved prediction intervals and simulations) any R Machine Learning model with misc::conformalize Mar 25, 2025
46. My poster for the 18th FINANCIAL RISKS INTERNATIONAL FORUM by Institut Louis Bachelier/Fondation du Risque/Europlace Institute of Finance Mar 19, 2025
47. Interpretable probabilistic kernel ridge regression using Matérn 3/2 kernels Mar 16, 2025
48. (News from) Probabilistic Forecasting of univariate and multivariate Time Series using Quasi-Randomized Neural Networks (Ridge2) and Conformal Prediction Mar 9, 2025
49. Word-Online: re-creating Karpathy's char-RNN (with supervised linear online learning of word embeddings) for text completion Mar 8, 2025
50. CRAN-like repository for most recent releases of Techtonique's R packages Mar 2, 2025
51. Presenting 'Online Probabilistic Estimation of Carbon Beta and Carbon Shapley Values for Financial and Climate Risk' at Institut Louis Bachelier Feb 27, 2025
52. Web app with DeepSeek R1 and Hugging Face API for chatting Feb 23, 2025
53. tisthemachinelearner: A Lightweight interface to scikit-learn with 2 classes, Classifier and Regressor (in Python and R) Feb 17, 2025
54. R version of survivalist: Probabilistic model-agnostic survival analysis using scikit-learn, xgboost, lightgbm (and conformal prediction) Feb 12, 2025
55. Model-agnostic global Survival Prediction of Patients with Myeloid Leukemia in QRT/Gustave Roussy Challenge (challengedata.ens.fr): Python's survivalist Quickstart Feb 10, 2025
56. A simple test of the martingale hypothesis in esgtoolkit Feb 3, 2025
57. Command Line Interface (CLI) for techtonique.net's API Jan 31, 2025
58. Gradient-Boosting and Boostrap aggregating anything (alert: high performance): Part5, easier install and Rust backend Jan 27, 2025
59. Just got a paper on conformal prediction REJECTED by International Journal of Forecasting despite evidence on 30,000 time series (and more). What's going on? Part2: 1311 time series from the Tourism competition Jan 20, 2025
60. Techtonique is out! (with a tutorial in various programming languages and formats) Jan 14, 2025
61. Univariate and Multivariate Probabilistic Forecasting with nnetsauce and TabPFN Jan 14, 2025
62. Just got a paper on conformal prediction REJECTED by International Journal of Forecasting despite evidence on 30,000 time series (and more). What's going on? Jan 5, 2025
63. Python and Interactive dashboard version of Stock price forecasting with Deep Learning: throwing power at the problem (and why it won't make you rich) Dec 31, 2024
64. Stock price forecasting with Deep Learning: throwing power at the problem (and why it won't make you rich) Dec 29, 2024
65. No-code Machine Learning Cross-validation and Interpretability in techtonique.net Dec 23, 2024
66. survivalist: Probabilistic model-agnostic survival analysis using scikit-learn, glmnet, xgboost, lightgbm, pytorch, keras, nnetsauce and mlsauce Dec 15, 2024
67. Model-agnostic 'Bayesian' optimization (for hyperparameter tuning) using conformalized surrogates in GPopt Dec 9, 2024
68. You can beat Forecasting LLMs (Large Language Models a.k.a foundation models) with nnetsauce.MTS Pt.2: Generic Gradient Boosting Dec 1, 2024
69. You can beat Forecasting LLMs (Large Language Models a.k.a foundation models) with nnetsauce.MTS Nov 24, 2024
70. Unified interface and conformal prediction (calibrated prediction intervals) for R package forecast (and 'affiliates') Nov 23, 2024
71. GLMNet in Python: Generalized Linear Models Nov 18, 2024
72. Gradient-Boosting anything (alert: high performance): Part4, Time series forecasting Nov 10, 2024
73. Predictive scenarios simulation in R, Python and Excel using Techtonique API Nov 3, 2024
74. Chat with your tabular data in www.techtonique.net Oct 30, 2024
75. Gradient-Boosting anything (alert: high performance): Part3, Histogram-based boosting Oct 28, 2024
76. R editor and SQL console (in addition to Python editors) in www.techtonique.net Oct 21, 2024
77. R and Python consoles + JupyterLite in www.techtonique.net Oct 15, 2024
78. Gradient-Boosting anything (alert: high performance): Part2, R version Oct 14, 2024
79. Gradient-Boosting anything (alert: high performance) Oct 6, 2024
80. Benchmarking 30 statistical/Machine Learning models on the VN1 Forecasting -- Accuracy challenge Oct 4, 2024
81. Automated random variable distribution inference using Kullback-Leibler divergence and simulating best-fitting distribution Oct 2, 2024
82. Forecasting in Excel using Techtonique's Machine Learning APIs under the hood Sep 30, 2024
83. Techtonique web app for data-driven decisions using Mathematics, Statistics, Machine Learning, and Data Visualization Sep 25, 2024
84. Parallel for loops (Map or Reduce) + New versions of nnetsauce and ahead Sep 16, 2024
85. Adaptive (online/streaming) learning with uncertainty quantification using Polyak averaging in learningmachine Sep 10, 2024
86. New versions of nnetsauce and ahead Sep 9, 2024
87. Prediction sets and prediction intervals for conformalized Auto XGBoost, Auto LightGBM, Auto CatBoost, Auto GradientBoosting Sep 2, 2024
88. Quick/automated R package development workflow (assuming you're using macOS or Linux) Part2 Aug 30, 2024
89. R package development workflow (assuming you're using macOS or Linux) Aug 27, 2024
90. A new method for deriving a nonparametric confidence interval for the mean Aug 26, 2024
91. Conformalized adaptive (online/streaming) learning using learningmachine in Python and R Aug 19, 2024
92. Bayesian (nonlinear) adaptive learning Aug 12, 2024
93. Auto XGBoost, Auto LightGBM, Auto CatBoost, Auto GradientBoosting Aug 5, 2024
94. Copulas for uncertainty quantification in time series forecasting Jul 28, 2024
95. Forecasting uncertainty: sequential split conformal prediction + Block bootstrap (web app) Jul 22, 2024
96. learningmachine for Python (new version) Jul 15, 2024
97. learningmachine v2.0.0: Machine Learning with explanations and uncertainty quantification Jul 8, 2024
98. My presentation at ISF 2024 conference (slides with nnetsauce probabilistic forecasting news) Jul 3, 2024
99. 10 uncertainty quantification methods in nnetsauce forecasting Jul 1, 2024
100. Forecasting with XGBoost embedded in Quasi-Randomized Neural Networks Jun 24, 2024
101. Forecasting Monthly Airline Passenger Numbers with Quasi-Randomized Neural Networks Jun 17, 2024
102. Automated hyperparameter tuning using any conformalized surrogate Jun 9, 2024
103. Recognizing handwritten digits with Ridge2Classifier Jun 3, 2024
104. Forecasting the Economy May 27, 2024
105. A detailed introduction to Deep Quasi-Randomized 'neural' networks May 19, 2024
106. Probability of receiving a loan; using learningmachine May 12, 2024
107. mlsauce's `v0.18.2`: various examples and benchmarks with dimension reduction May 6, 2024
108. mlsauce's `v0.17.0`: boosting with Elastic Net, polynomials and heterogeneity in explanatory variables Apr 29, 2024
109. mlsauce's `v0.13.0`: taking into account inputs heterogeneity through clustering Apr 21, 2024
110. mlsauce's `v0.12.0`: prediction intervals for LSBoostRegressor Apr 15, 2024
111. Conformalized predictive simulations for univariate time series on more than 250 data sets Apr 7, 2024
112. learningmachine v1.1.2: for Python Apr 1, 2024
113. learningmachine v1.0.0: prediction intervals around the probability of the event 'a tumor being malignant' Mar 25, 2024
114. Bayesian inference and conformal prediction (prediction intervals) in nnetsauce v0.18.1 Mar 18, 2024
115. Multiple examples of Machine Learning forecasting with ahead Mar 11, 2024
116. rtopy (v0.1.1): calling R functions in Python Mar 4, 2024
117. ahead forecasting (v0.10.0): fast time series model calibration and Python plots Feb 26, 2024
118. A plethora of datasets at your fingertips Part3: how many times do couples cheat on each other? Feb 19, 2024
119. nnetsauce's introduction as of 2024-02-11 (new version 0.17.0) Feb 11, 2024
120. Tuning Machine Learning models with GPopt's new version Part 2 Feb 5, 2024
121. Tuning Machine Learning models with GPopt's new version Jan 29, 2024
122. Subsampling continuous and discrete response variables Jan 22, 2024
123. DeepMTS, a Deep Learning Model for Multivariate Time Series Jan 15, 2024
124. A classifier that's very accurate (and deep) Pt.2: there are > 90 classifiers in nnetsauce Jan 8, 2024
125. learningmachine: prediction intervals for conformalized Kernel ridge regression and Random Forest Jan 1, 2024
126. A plethora of datasets at your fingertips Part2: how many times do couples cheat on each other? Descriptive analytics, interpretability and prediction intervals using conformal prediction Dec 25, 2023
127. Diffusion models in Python with esgtoolkit (Part2) Dec 18, 2023
128. Diffusion models in Python with esgtoolkit Dec 11, 2023
129. Julia packaging at the command line Dec 4, 2023
130. Quasi-randomized nnetworks in Julia, Python and R Nov 27, 2023
131. A plethora of datasets at your fingertips Nov 20, 2023
132. A classifier that's very accurate (and deep) Nov 12, 2023
133. mlsauce version 0.8.10: Statistical/Machine Learning with Python and R Nov 5, 2023
134. AutoML in nnetsauce (randomized and quasi-randomized nnetworks) Pt.2: multivariate time series forecasting Oct 29, 2023
135. AutoML in nnetsauce (randomized and quasi-randomized nnetworks) Oct 22, 2023
136. Version v0.14.0 of nnetsauce for R and Python Oct 16, 2023
137. A diffusion model: G2++ Oct 9, 2023
138. Diffusion models in ESGtoolkit + announcements Oct 2, 2023
139. An infinity of time series forecasting models in nnetsauce (Part 2 with uncertainty quantification) Sep 25, 2023
140. (News from) forecasting in Python with ahead (progress bars and plots) Sep 18, 2023
141. Forecasting in Python with ahead Sep 11, 2023
142. Risk-neutralize simulations Sep 4, 2023
143. Comparing cross-validation results using crossval_ml and boxplots Aug 27, 2023
144. Reminder Apr 30, 2023
145. Did you ask ChatGPT about who you are? Apr 16, 2023
146. A new version of nnetsauce (randomized and quasi-randomized 'neural' networks) Apr 2, 2023
147. Simple interfaces to the forecasting API Nov 23, 2022
148. A web application for forecasting in Python, R, Ruby, C#, JavaScript, PHP, Go, Rust, Java, MATLAB, etc. Nov 2, 2022
149. Prediction intervals (not only) for Boosted Configuration Networks in Python Oct 5, 2022
150. Boosted Configuration (neural) Networks Pt. 2 Sep 3, 2022
151. Boosted Configuration (_neural_) Networks for classification Jul 21, 2022
152. A Machine Learning workflow using Techtonique Jun 6, 2022
153. Super Mario Bros © in the browser using PyScript May 8, 2022
154. News from ESGtoolkit, ycinterextra, and nnetsauce Apr 4, 2022
155. Explaining a Keras _neural_ network predictions with the-teller Mar 11, 2022
156. New version of nnetsauce -- various quasi-randomized networks Feb 12, 2022
157. A dashboard illustrating bivariate time series forecasting with `ahead` Jan 14, 2022
158. Hundreds of Statistical/Machine Learning models for univariate time series, using ahead, ranger, xgboost, and caret Dec 20, 2021
159. Forecasting with `ahead` (Python version) Dec 13, 2021
160. Tuning and interpreting LSBoost Nov 15, 2021
161. Time series cross-validation using `crossvalidation` (Part 2) Nov 7, 2021
162. Fast and scalable forecasting with ahead::ridge2f Oct 31, 2021
163. Automatic Forecasting with `ahead::dynrmf` and Ridge regression Oct 22, 2021
164. Forecasting with `ahead` Oct 15, 2021
165. Classification using linear regression Sep 26, 2021
166. `crossvalidation` and random search for calibrating support vector machines Aug 6, 2021
167. parallel grid search cross-validation using `crossvalidation` Jul 31, 2021
168. `crossvalidation` on R-universe, plus a classification example Jul 23, 2021
169. Documentation and source code for GPopt, a package for Bayesian optimization Jul 2, 2021
170. Hyperparameters tuning with GPopt Jun 11, 2021
171. A forecasting tool (API) with examples in curl, R, Python May 28, 2021
172. Bayesian Optimization with GPopt Part 2 (save and resume) Apr 30, 2021
173. Bayesian Optimization with GPopt Apr 16, 2021
174. Compatibility of nnetsauce and mlsauce with scikit-learn Mar 26, 2021
175. Explaining xgboost predictions with the teller Mar 12, 2021
176. An infinity of time series models in nnetsauce Mar 6, 2021
177. New activation functions in mlsauce's LSBoost Feb 12, 2021
178. 2020 recap, Gradient Boosting, Generalized Linear Models, AdaOpt with nnetsauce and mlsauce Dec 29, 2020
179. A deeper learning architecture in nnetsauce Dec 18, 2020
180. Classify penguins with nnetsauce's MultitaskClassifier Dec 11, 2020
181. Bayesian forecasting for uni/multivariate time series Dec 4, 2020
182. Generalized nonlinear models in nnetsauce Nov 28, 2020
183. Boosting nonlinear penalized least squares Nov 21, 2020
184. Statistical/Machine Learning explainability using Kernel Ridge Regression surrogates Nov 6, 2020
185. NEWS Oct 30, 2020
186. A glimpse into my PhD journey Oct 23, 2020
187. Submitting R package to CRAN Oct 16, 2020
188. Simulation of dependent variables in ESGtoolkit Oct 9, 2020
189. Forecasting lung disease progression Oct 2, 2020
190. New nnetsauce Sep 25, 2020
191. Technical documentation Sep 18, 2020
192. A new version of nnetsauce, and a new Techtonique website Sep 11, 2020
193. Back next week, and a few announcements Sep 4, 2020
194. Explainable 'AI' using Gradient Boosted randomized networks Pt2 (the Lasso) Jul 31, 2020
195. LSBoost: Explainable 'AI' using Gradient Boosted randomized networks (with examples in R and Python) Jul 24, 2020
196. nnetsauce version 0.5.0, randomized neural networks on GPU Jul 17, 2020
197. Maximizing your tip as a waiter (Part 2) Jul 10, 2020
198. New version of mlsauce, with Gradient Boosted randomized networks and stump decision trees Jul 3, 2020
199. Announcements Jun 26, 2020
200. Parallel AdaOpt classification Jun 19, 2020
201. Comments section and other news Jun 12, 2020
202. Maximizing your tip as a waiter Jun 5, 2020
203. AdaOpt classification on MNIST handwritten digits (without preprocessing) May 29, 2020
204. AdaOpt (a probabilistic classifier based on a mix of multivariable optimization and nearest neighbors) for R May 22, 2020
205. AdaOpt May 15, 2020
206. Custom errors for cross-validation using crossval::crossval_ml May 8, 2020
207. Documentation+Pypi for the `teller`, a model-agnostic tool for Machine Learning explainability May 1, 2020
208. Encoding your categorical variables based on the response variable and correlations Apr 24, 2020
209. Linear model, xgboost and randomForest cross-validation using crossval::crossval_ml Apr 17, 2020
210. Grid search cross-validation using crossval Apr 10, 2020
211. Documentation for the querier, a query language for Data Frames Apr 3, 2020
212. Time series cross-validation using crossval Mar 27, 2020
213. On model specification, identification, degrees of freedom and regularization Mar 20, 2020
214. Import data into the querier (now on Pypi), a query language for Data Frames Mar 13, 2020
215. R notebooks for nnetsauce Mar 6, 2020
216. Version 0.4.0 of nnetsauce, with fruits and breast cancer classification Feb 28, 2020
217. Create a specific feed in your Jekyll blog Feb 21, 2020
218. Git/Github for contributing to package development Feb 14, 2020
219. Feedback forms for contributing Feb 7, 2020
220. nnetsauce for R Jan 31, 2020
221. A new version of nnetsauce (v0.3.1) Jan 24, 2020
222. ESGtoolkit, a tool for Monte Carlo simulation (v0.2.0) Jan 17, 2020
223. Search bar, new year 2020 Jan 10, 2020
224. 2019 Recap, the nnetsauce, the teller and the querier Dec 20, 2019
225. Understanding model interactions with the `teller` Dec 13, 2019
226. Using the `teller` on a classifier Dec 6, 2019
227. Benchmarking the querier's verbs Nov 29, 2019
228. Composing the querier's verbs for data wrangling Nov 22, 2019
229. Comparing and explaining model predictions with the teller Nov 15, 2019
230. Tests for the significance of marginal effects in the teller Nov 8, 2019
231. Introducing the teller Nov 1, 2019
232. Introducing the querier Oct 25, 2019
233. Prediction intervals for nnetsauce models Oct 18, 2019
234. Using R in Python for statistical learning/data science Oct 11, 2019
235. Model calibration with `crossval` Oct 4, 2019
236. Bagging in the nnetsauce Sep 25, 2019
237. Adaboost learning with nnetsauce Sep 18, 2019
238. Change in blog's presentation Sep 4, 2019
239. nnetsauce on Pypi Jun 5, 2019
240. More nnetsauce (examples of use) May 9, 2019
241. nnetsauce Mar 13, 2019
242. crossval Mar 13, 2019
243. test Mar 10, 2019