https://hackerpaper.kaipfister.de/p/1210.7273/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMThttps://news.ycombinator.com/item?id=40258342urn:hackerpapers:mention:1210.7273:40258342Sat, 04 May 2024 15:26:07 GMT<p>https://arxiv.org/abs/1210.7273 In the article &quot;Distilling free-form natural laws from experimental data&quot;, Schmidt and Lipson introduced the idea that free-form natural laws can be learned from experimental measurements in a physical system using symbolic (genetic) regression algorithms. An important claim in this work is that the algorithm finds laws in data without having incorporated any prior knowledge of physics. Upon close inspection, however, we show that their method implicitly incorporates Hamilton&#x27;s equations of motions and Newton&#x27;s second law, demystifying how they are able to find…</p><p><a href="https://hackerpaper.kaipfister.de/p/1210.7273/">Paper and discussion history</a>. A mention is not an endorsement.</p>nlin.AO