Sign in

Christoph Molnar

@christophmolnar.bsky.social
6.2K followers 966 following 143 posts

Author of Interpretable Machine Learning and other books Newsletter: mindfulmodeler.substack.com Website: christophmolnar.com

PostsRepliesMedia
Christoph Molnar @christophmolnar.bsky.social · 08/07/2025
Using feature importance to interpret your models? This paper might be of interest to you. Papers by @gunnark.bsky.social are always worth checking out.
15272
Christoph Molnar @christophmolnar.bsky.social · 08/04/2025
My stock portfolio is deep in the red, and tariffs by the Trump admin might be the cause. Could an LLM have been used to calculate them? It made me rethink how LLMs shape decisions, from big global-economy-wrecking ones to everyday decisions.
mindfulmodeler.substack.com
Who’s Really Making the Decisions?
LLMs, tariffs, and the silent takeover of decisions
3113
Christoph Molnar @christophmolnar.bsky.social · 01/04/2025
SHAP interpretations depend on background data — change the data, change the explanation. A critical but often overlooked issue in model interpretability. Read more:
mindfulmodeler.substack.com
SHAP Interpretations Depend on Background Data — Here’s Why
Or why height doesn't matter in the NBA
0121
Christoph Molnar @christophmolnar.bsky.social · 28/03/2025
I recently joined The AI Fundamentalists with my co-author Timo Freiesleben to discuss our book Supervised Machine Learning for Science. We explored how scientists can leverage ML while maintaining rigor and embedding domain knowledge.
buzzsprout.com
Supervised machine learning for science with Christoph Molnar and Timo Freiesleben, Part 1 - The AI Fundamentalists
Machine learning is transforming scientific research across disciplines, but many scientists remain skeptical about using approaches that focus on prediction over causal understanding. That’s why...
1110
Christoph Molnar @christophmolnar.bsky.social · 13/03/2025
The 3rd edition of Interpretable Machine Learning is out! 🎉 Major cleanup, better examples, and new chapters on Data & Models, Interpretability Goals, Ceteris Paribus, and LOFO Importance. The book remains free to read for everyone. But you can also buy ebook or paperback.
0163
Christoph Molnar @christophmolnar.bsky.social · 12/03/2025
Has anyone seen Counterfactual Explanations for machine learning models somewhere in the wild? They are often discussed in research papers, but I have yet to see them being used somewhere in an actual process or product.
1101
Christoph Molnar @christophmolnar.bsky.social · 12/03/2025
Trying Claude Code for some tasks. Paradoxically, it's most expensive when it doesn't work because it fails, then tries a couple of times again, burning through tokens. So sometimes it's 20 cents for saving you 20 minutes of work. Other times it's $1 for wasting 10 minutes.
2763
Christoph Molnar @christophmolnar.bsky.social · 07/03/2025
Only waiting for the print proof, but if it looks good, I'll publish the third edition of Interpretable Machine Learning next week. As always, it was more work than anticipated—especially moving the entire book project from Bookdown to Quarto, which took a bit of effort.
1180
Christoph Molnar @christophmolnar.bsky.social · 25/02/2025
Can an office game outperform machine learning? My most recent post on Mindful Modeler dives into the wisdom of the crowds and prediction markets. Read the full story here:
buff.ly
Can an office game outperform machine learning?
Wisdom of the crowds, prediction markets, and more fun in the work place.
050
Christoph Molnar @christophmolnar.bsky.social · 04/02/2025
A year ago, I took a risk & spent quite some time on a ML competition. It paid off—I won 4th place overall & 1st in explainability! Here's a summary of the journey, challenges, & key insights from my winning solution (water supply forecasting)
1221
Christoph Molnar @christophmolnar.bsky.social · 29/01/2025
OpenAI right now
double button meme. Guy (labeled openai) presses two buttons simultaneously. First one says "Training on other's work is okay" The other says it's not okay
210717
Christoph Molnar @christophmolnar.bsky.social · 22/01/2025
The original SHAP paper has been cited over 30k times. The paper showed that attribution methods, like LIME and LRP, compute Shapley values (with some adaptations). The paper also introduces estimation methods for Shapley values, like KernelSHAP, which today is deprecated.
3262
Christoph Molnar @christophmolnar.bsky.social · 21/01/2025
To this day, the Interpretable Machine Learning book is still my most impactful project. But as time went on, I dreaded working on it. Fortunately, I found the motivation again and I'm working on the 3rd edition. 😁 Read more here:
buff.ly
Why I almost stopped working on Interpretable Machine Learning
7 years ago I started writing the book Interpretable Machine Learning.
1213
Christoph Molnar @christophmolnar.bsky.social · 14/01/2025
How I sometimes feel working on "traditional" machine learning topics instead of generative AI stuff 😂
the "They don't know meme". Party. Awkward guy in the corner saying They don't know I work on the 3rd edition of Interpretable Machine Learning". Rest is having fun, titled "Everyone else talking about generative AI"
1415
Christoph Molnar @christophmolnar.bsky.social · 17/12/2024
It's quite ironic how people who built the best prediction models are such bad predictors themselves. They throw all their knowledge about how to make good predictions overboard and just claim things like: AI will replace radiologists in a few years or when they expect AGI.
1211
Christoph Molnar @christophmolnar.bsky.social · 17/12/2024
The problem with all these AI demos (especially for image and video generation): They are the most impressive, cherry-picked examples. That includes cherry-picking prompts and themes that produced better results. But as a user, you want good results for every prompt/theme relevant to your use case
3211
Christoph Molnar @christophmolnar.bsky.social · 13/12/2024
Looking for a Christmas gift for a stubborn Bayesian or an over-hyped AI enthusiast? Modeling Mindsets is a short read to broaden your perspective on data modeling. christophmolnar.com/books/modeli... *Hat not included.
Cover of Modeling Mindsets book. The octopus on the cover has a Christmas hat on. Still looks a bit creepy though.
3112
Christoph Molnar @christophmolnar.bsky.social · 13/12/2024
My personal rules for AI-assisted writing: • Use AI only for small and specific stuff, like grammar fixes or making suggestions for factual corrections. • Never let an LLM change voice and tone. • I review any changes made by AI.
2141
Christoph Molnar @christophmolnar.bsky.social · 13/12/2024
What a sad timeline, where vaccines — one of medicine's clearest wins with all upside and minimal downside — have become targets. Can't we have like an anti-knee arthroscopy movement or whatever instead?
3140
Christoph Molnar @christophmolnar.bsky.social · 04/12/2024
Citing a non-deterministic, "hallucinating", and non-reproducible LLM output is wild. While the norms and best practices are evolving, citing them seems the wrong way. (even wilder when some people add "ChatGPT" as their co-authors)
4223
Christoph Molnar @christophmolnar.bsky.social · 03/12/2024
What are shapley interactions and why should you care about them? This is a guest post by Julia, Max, Fabian and Hubert on my newsletter Mindful Modeler. I also learned a lot from this post and definitely recommend checking out the shapiq package. mindfulmodeler.substack.com/p/what-are-s...
mindfulmodeler.substack.com
What Are Shapley Interactions, and Why Should You Care?
A guest post by Julia, Max, Fabian and Hubert.
1362
Christoph Molnar @christophmolnar.bsky.social · 29/11/2024
Is anyone aware of a completely AI-generated book that people actually read? Excluding books that are dedicated "AI experiments" and where the book is more about the experiment. Also excluding AI-assisted books where generative AI played a minor role
190
Christoph Molnar @christophmolnar.bsky.social · 27/11/2024
The unofficial GIF-based pandas library documentation. pandas.DataFrame.rolling
media.tenor.com
a panda bear is laying down in the grass .
Alt: a panda bear is rolling down in the grass. It's a side-ways roll, hlding some type of object. I give 10/10.
3546
Christoph Molnar @christophmolnar.bsky.social · 27/11/2024
Without non-linear activation functions, neural networks would be linear models, no matter how many layers are stacked.
Mathematical proof that a weighte sum of weighted sums is again a weighted sum.
3361
Christoph Molnar @christophmolnar.bsky.social · 27/11/2024
Got myself a Samsung Galaxy S9 tablet for note-taking, and I love it. (and yes, I'm reading my own book here as a reference for another project, feeling like an imposter because I don't have everything memorized 😂)
Photo of tablet and my hand using the pen to highlight sections of a PDF.
3260
Christoph Molnar @christophmolnar.bsky.social · 27/11/2024
I'm always amazed at how popular the random forest algorithm is for remote sensing research. I would have expected deep learning to be more popular there (not to say it isn't). Must be an attraction to trees. 😁
Paper title: Random forest in remote sensing: A review of applications and future directions

Authors: Mariana Belgiu a, Lucian Drăguţ 

Abstract: A random forest (RF) classifier is an ensemble classifier that produces multiple decision trees, using a randomly selected subset of training samples and variables. This classifier has become popular within the remote sensing community due to the accuracy of its classifications. The overall objective of this work was to review the utilization of RF classifier in remote sensing. This review has revealed that RF classifier can successfully handle high data dimensionality and multicolinearity, being both fast and insensitive to overfitting. It is, however, sensitive to the sampling design. The variable importance (VI) measurement provided by the RF classifier has been extensively exploited in different scenarios, for example to reduce the number of dimensions of hyperspectral data, to identify the most relevant multisource remote sensing and geographic data, and to select the most suitable season to classify particular target classes. Further investigations are required into less commonly exploited uses of this classifier, such as for sample proximity analysis to detect and remove outliers in the training samples.
5250
Christoph Molnar @christophmolnar.bsky.social · 26/11/2024
What's the difference between explainability and interpretability? Does the machine learning community have an agreed-upon definition? No. There's a great overview, which is from this paper: arxiv.org/abs/2211.08943 My take: I prefer interpretability since the term explainability is too strong.
Overview of definitions for interpretability and explainability for different papers. The gist: the authors have different definitions.
39119
Reposted by Christoph Molnar
Juan Mateos-Garcia @jmateosgarcia.bsky.social · 26/11/2024
AI for science could be more impactful than chatbots. It is already helping win Nobel prizes and accelerating drug development and materials discovery. Today we published an essay about it: why it matters, how it’s happening and its implications. Here is a summary from an econ / social sci lens.
27930
Christoph Molnar @christophmolnar.bsky.social · 26/11/2024
Machine learning and statistics have very narrow ideas of what a model is and how to abstract the world. To broaden the "model" horizon, I can recommend these two books: • Thinking in Systems by Donella H. Meadows • Simulation and Similarity by Michael Weisberg (ignore the monkey)
Me holding the two mentioned books into the camera. In the background there is a plush monkey sitting on a mounted guitar, peaking over the books, potentially distracting the viewer from the books. I still like the monkey.
3490
Christoph Molnar @christophmolnar.bsky.social · 24/11/2024
No one can explain stochastic gradient descent better than this panda.
media.tenor.com
a panda bear is rolling around in the grass in a zoo enclosure .
Alt: a panda bear is rolling around in the grass in a zoo enclosure .
1021632
Christoph Molnar @christophmolnar.bsky.social · 24/11/2024
Looking for a nice classification dataset? There's a cute alternative to Iris: The Palmer penguins dataset Find the data here: github.com/allisonhorst... Artwork by @allisonhorst.bsky.social
github.com
GitHub - allisonhorst/palmerpenguins: A great intro dataset for data exploration & visualization (alternative to iris).
A great intro dataset for data exploration & visualization (alternative to iris). - allisonhorst/palmerpenguins
2393
Christoph Molnar @christophmolnar.bsky.social · 24/11/2024
I feel like not enough people know about Quarto for creating documents. How it works: Write in markdown and use Quarto to convert it to html, pdf, epub, ... I produce my books with Quarto (web + ebook + print version). But you can also use it for websites, reports, dashboards, ... quarto.org
quarto.org
Quarto
An open source technical publishing system for creating beautiful articles, websites, blogs, books, slides, and more. Supports Python, R, Julia, and JavaScript.
1618026
Christoph Molnar @christophmolnar.bsky.social · 24/11/2024
Writing my Master's thesis: "I hate writing." Starting my first book: "Writing is fun! Maybe I should do a PhD." During my PhD: "I hate writing." Turns out, I hate writing papers but love writing books. Glad I made the career jump from academia to writer!
1300
Christoph Molnar @christophmolnar.bsky.social · 24/11/2024
Optimist: the cup is half full Pessimist: the cup is half empty Statistician: The cup's content is a random variable. Let's assume a Beta distribution and I need a few more cups to tell you more about how full they are.
060
Christoph Molnar @christophmolnar.bsky.social · 22/11/2024
Just realized BlueSky allows sharing valuable stuff cause it doesn't punish links. 🤩 Let's start with "What are embeddings" by @vickiboykis.com The book is a great summary of embeddings, from history to modern approaches. The best part: it's free. Link: vickiboykis.com/what_are_emb...
Book outlineOver the past decade, embeddings — numerical representations of
machine learning features used as input to deep learning models — have
become a foundational data structure in industrial machine learning
systems. TF-IDF, PCA, and one-hot encoding have always been key tools
in machine learning systems as ways to compress and make sense of
large amounts of textual data. However, traditional approaches were
limited in the amount of context they could reason about with increasing
amounts of data. As the volume, velocity, and variety of data captured
by modern applications has exploded, creating approaches specifically
tailored to scale has become increasingly important.
Google’s Word2Vec paper made an important step in moving from
simple statistical representations to semantic meaning of words. The
subsequent rise of the Transformer architecture and transfer learning, as
well as the latest surge in generative methods has enabled the growth
of embeddings as a foundational machine learning data structure. This
survey paper aims to provide a deep dive into what embeddings are,
their history, and usage patterns in industry.Cover image
22647101
Christoph Molnar @christophmolnar.bsky.social · 21/11/2024
More and more ML people are now posting on Twitter about switching to Bluesky, and these last few days, Bluesky was my number one social media platform (sorry, LinkedIn). Really feels like a tipping point (at least for my bubble).
71013
Christoph Molnar @christophmolnar.bsky.social · 21/11/2024
That's the way. Consistency is overhyped. The irregularities keep the coder alert and creative.
050
Reposted by Christoph Molnar
Maike Osborne @maosbot.bsky.social · 09/11/2024
New here? Interested in AI/ML? Check out these great starter packs! AI: go.bsky.app/SipA7it RL: go.bsky.app/3WPHcHg Women in AI: go.bsky.app/LaGDpqg NLP: go.bsky.app/SngwGeS AI and news: go.bsky.app/5sFqVNS You can also search all starter packs here: blueskydirectory.com/starter-pack...
66557212
Reposted by Christoph Molnar
TRIPOD Statement @tripodstatement.bsky.social · 19/11/2024
Our latest recommendations for reporting #AI/#machinelearning prediction model studies in healthcare are available in the @bmj.com bmj.com/content/385/... Don't forget the further guidance for each reporting recommendation in the supplementary material #MLSky #statsSky #reportingstandards
42815
Reposted by Christoph Molnar
Willie Neiswanger @willieneis.bsky.social · 20/11/2024
The first list filled up, so here's a second list of AI for Science researchers on bluesky. Let me know if I missed you / if you'd like to join! bsky.app/starter-pack...
577129
Christoph Molnar @christophmolnar.bsky.social · 20/11/2024
Even as an interpretable ML researcher, I wasn't sure what to make of Mechanistic Interpretability, which seemed to come out of nowhere not too long ago. But then I found the paper "Mechanistic?" by @nsaphra.bsky.social and @sarah-nlp.bsky.social, which clarified things.
Screenshot of the paper.
723026
Christoph Molnar @christophmolnar.bsky.social · 19/11/2024
After years of writing with Vim, it's finally time to write my books in a modern editor. Time to enter the 21st century of editors. A new era of writing. A new me.
Text that says "$ brew install neovim"
3331
Christoph Molnar @christophmolnar.bsky.social · 19/11/2024
As a machine learning community, we are obsessed with benchmarks. A short rant in the latest issue of Mindful Modeler:
buff.ly
We are obsessed with benchmarks
Two days ago, I talked to a causal ML researcher.
160
Christoph Molnar @christophmolnar.bsky.social · 19/11/2024
I love random forests
0151
Christoph Molnar @christophmolnar.bsky.social · 19/11/2024
That's such a simple yet great idea for a reference book for any machine learning person. The first pages look very promising, I love the visuals for the metrics:
1275
Christoph Molnar @christophmolnar.bsky.social · 18/11/2024
Had a discussion with a Causal ML researcher yesterday. They have trouble publishing because reviewers always want benchmarks, which don't make sense for many causal questions. I had the same troubles with publishing interpretability research.
3110
Christoph Molnar @christophmolnar.bsky.social · 15/11/2024
Interested in machine learning in science? Timo and I recently published a book, and even if you are not a scientist, you'll find useful overviews of topics like causality and robustness. The best part is that you can read it for free: ml-science-book.com
712929
Reposted by Christoph Molnar
Federico Adolfi @fedeadolfi.bsky.social · 14/11/2024
A starter pack of people working on interpretability / explainability of all kinds, using theoretical and/or empirical approaches. Reply or DM if you want to be added, and help me reach others! go.bsky.app/DZv6TSS
348026
Christoph Molnar @christophmolnar.bsky.social · 14/11/2024
These starter packs were super helpful to connect with the ML/AI community. Highly recommended:
0103
Christoph Molnar @christophmolnar.bsky.social · 14/11/2024
Working on the 3rd edition of Interpretable Machine Learning. My first approach was to just add a few chapters, update some sections. As I go deeper, I realize I go fully into "rewrite" mode. Had to add a reminder not to rewrite the entire book 😂
040