Creează un cont pentru a te abona la acest blog și a-i urmări articolele pe pagina Lectură.
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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.
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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.
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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…
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Causal Inference workers are often stymied when calculating probabilities from large Bayesian Networks, so new ways of dealing with large DAGs are very desirable.
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I’ve decided to write a new (free, open source) book entitled “Bayesuvius Quantico” about quantum Bayesian networks (qbnets).
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On April 11, I announced the Mappa Mundi Causal Genomics Challenge, which involves discovering a causal DAG for the DREAM3 dataset.
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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.
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https://x.com/i/grok?
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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.
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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”.