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A blog post sharing links and resources about AI applications in mathematics and physics, with the author openly admitting they lack deep expertise on the topic. The post primarily serves as a pointer to a "Future of Mathematics" event at Stanford and invites knowledgeable reader
This article presents a mathematical study of colourings in uniform group divisible designs and maximum packings. It defines weak c-colourings (assigning colours to points so no block is monochromatic) and block-equitable colourings (where each block has a balanced distribution o



This article explains the theoretical foundations of statistical learning theory, specifically addressing when learning from data is guaranteed to work. It builds from first principles—starting with Markov's inequality and Hoeffding's lemma—to prove the Fundamental Theorem of Statistical Learning, which states that a hypothesis class is learnable if and only

Doron Zeilberger's 82nd opinion piece argues that good lemmas are more valuable than theorems, using Szemerédi's Regularity Lemma as his prime example. He contends that while theorems are often dead ends, a powerful lemma can lead to multiple major discoveries (like Fields medals) and has far greater lasting impact in mathematics.
Think Linear Algebra is a code-first, case-based educational book that teaches linear algebra through real-world problems and Python programming. Rather than focusing on abstract theory, each chapter tackles practical challenges such as modeling web traffic, simulating flocking birds, or analyzing electrical circuits. Readers use Python libraries like NumPy,
