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  1. My new software “not-do-calculus”

    Check out my new free open source software https://github.com/rrtucci/not-do-calculus not-do-calculus does everything my previous software dag_iden_detector (released exactly one month ago) does plus it can do much much more.

  2. Check out my new free open source software https://github.com/rrtucci/dag_iden_detector dag_iden_detector is a Python program for detecting whether an adjustment formula obtained using Judea Pearl’s Do Calculus is correct or not.

  3. SERE paper on Causal LLM ology

    Checkout this new paper (published in ArXiv on May 5, 2026) from China https://arxiv.org/pdf/2605.03701 SERE: Structural Example Retrieval for Enhancing LLMs in Event Causality Identification, by Zhifeng Hao, Zhongjie Chen, Junhao Lu, Shengyin Yu, Guimin…

  4. Causal Inference workers are often stymied when calculating probabilities from large Bayesian Networks, so new ways of dealing with large DAGs are very desirable.

  5. Bayesuvius Quantico

    I’ve decided to write a new (free, open source) book entitled “Bayesuvius Quantico” about quantum Bayesian networks (qbnets).

  6. On April 11, I announced the Mappa Mundi Causal Genomics Challenge, which involves discovering a causal DAG for the DREAM3 dataset.

  7. The Mappa Mundi Causal Genomics Challenge

    Recently, I became interested in trying to discover a Causal DAG for the human genome (~21,000 genes), in order to find genetic causes and cures of diseases.

  8. https://x.com/i/grok?

  9. https://t.co/baBM1RfLq8 — http://www.ar-tiste.xyz (@artistexyz) March 22, 2025 I’m storing here a conversation I had with Grok on March 22 in case it disappears.

  10. Update on Gene_Causal_Mapper software

    In a previous blog post, I mentioned that I had written a paper entitled: “Discovering a Causal DAG for genes via the Mappa Mundi algorithm”.