
Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects
The paper discusses the application of artificial intelligence in solving inverse partial differential equation (PDE) problems, which are crucial in various scientific fields. It categorizes these problems into inverse problems, inverse design, and control problems, providing a review of recent methodologies and applications. The authors also highlight future challenges and prospects in this area, emphasizing the transformative impact of AI on traditional approaches.
- ▪Inverse PDE problems are significant in fields such as medical imaging, geophysics, and materials science.
- ▪The paper categorizes inverse PDE problems into three main areas: inverse problems, inverse design, and control problems.
- ▪The authors review state-of-the-art approaches and summarize applications across various scientific and industrial domains.
arXiv cs.AI files mainly under ai research. We currently carry 1,128 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.16966 |
| Publication time | Tue, 19 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-19T04:04:57.272Z |
| Last seen | 2026-05-19T04:04:57.272Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | PrgIgqDcXudC |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2605.16966 (cs) [Submitted on 16 May 2026] Title:Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects Authors:Zhentao Tan, Yuze Hao, Boyi Zou, Mingsheng Long, Yi Yang, Gang Bao View a PDF of the paper titled Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects, by Zhentao Tan and 5 other authors View PDF HTML (experimental) Abstract:Solving inverse partial differential equation (PDE) problems is a fundamental topic in scientific research due to its broad significance across a wide range of real-world applications.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.